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Article

Factors Affecting Conflict Resolution Capacity: An Organizational Perspective from Construction Firms

by
Marcelo Villena Manzanares
1,* and
Francisco Villena Manzanares
2
1
Department of Construction Engineering and Engineering Projects, University of Seville, 41092 Seville, Spain
2
Design Engineering Department, Polytechnic School, University of Seville, 41011 Seville, Spain
*
Author to whom correspondence should be addressed.
Buildings 2026, 16(12), 2471; https://doi.org/10.3390/buildings16122471
Submission received: 16 April 2026 / Revised: 9 June 2026 / Accepted: 12 June 2026 / Published: 22 June 2026
(This article belongs to the Special Issue Application of Digital Technology and AI in Construction Management)
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Abstract

Construction management, from the contractor’s perspective, is led by the Construction Manager (CM). The work motivation and leadership style of the CM are critical variables for the successful execution of construction projects. The scientific literature identifies participative leadership as the most effective style for mitigating conflicts among various stakeholders. However, analyzing the specific variables that influence a CM’s conflict resolution capacity remains an underexplored area. Furthermore, while the CM must act as a leader for their team (subcontractors, suppliers, etc.), they remain accountable to the contractor’s senior management. Therefore, this study aims to analyze the mediating role of CM motivation in the relationship between leadership and conflict resolution capacity using Partial Least Squares Structural Equation Modeling (PLS-SEM). In the construction industry, conflict resolution is not merely a situational fix but a critical process of capturing and externalizing tacit knowledge. Knowledge management and the ability to resolve conflicts in the construction sector are directly linked, critical, and strategic in nature. Construction is an industry characterized by fragmentation, the temporary nature of its projects, diversity of stakeholders (developers, builders, subcontractors, engineering firms) and a high level of uncertainty. In this environment, conflict is virtually inevitable. However, the way in which a CM handles a conflict determines whether it becomes a destructive dispute or an opportunity for improvement.

1. Introduction

Work motivation and leadership of the CM have become fundamental concepts influencing performance. Although motivation remains understudied in the construction sector, some research has been applied specifically to construction workers [1]. However, the CM is the professional representing the contractor—typically holding a university degree in architecture or engineering—who is responsible for the physical execution of infrastructure, whether in civil engineering or building construction. CMs exercise leadership in their daily work by managing diverse teams. In summary, the work motivation and leadership style exercised by the Site Manager are critical factors affecting project performance. In the existing literature, the leadership of the CM has not been fully developed by researchers [2]; however, scholarly work does recognize that a participative (democratic) and flexible leadership style is more effective at resolving conflicts. To address this gap, the objective of this study is to analyze—through structural equation modeling—the relationship between participative leadership, motivation, and the CM’s conflict resolution capacity. This study was conducted within the Spanish construction sector. In this context, the present research aims to answer the following primary research question focusing on the CM: What impact does participative leadership have on conflict resolution capacity, and what role does motivation play? Despite the existing literature on leadership and construction management, there is still no direct evidence of effective leadership skills applied specifically to CMs in the Spanish construction sector. Despite the existing literature, the internal psychological mechanisms and the mediating role of motivation in CMs’ conflict resolution capacity remain understudied, particularly within the specific framework of the Spanish construction sector. This study examines the relationship between participative leadership and conflict resolution capacity in the construction industry, specifically analyzing the mediating role of the CM’s motivation. A quantitative approach was used, collecting data from 118 CPMs. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). This method is the preferred approach when the primary objective of the research is the prediction and explanation of target constructs, or when the underlying theoretical framework is still under development. This research provides empirical evidence that, while participative leadership is a dominant tool for managing disputes, its effectiveness is significantly amplified when it succeeds in enhancing the CPM’s motivational state. The paper is organized as follows: Section 2 provides the conceptual framework; Section 3 presents the conceptual model and hypothesis development; Section 4 describes the research methodology, data analysis, and results; finally, the last section presents the conclusions, including contributions, limitations, and future research directions.

2. Conceptual Framework

Despite the extensive literature on leadership in project management, most research has focused on the direct impact of leadership style on technical performance, often ignoring the underlying psychological mechanisms that activate such performance [3]. In the construction sector, characterized by a hierarchical and adversarial work culture, there is a critical gap in understanding how the intrinsic factors of the CM influence their dispute resolution capacity.

2.1. CM Skills

From the contractor’s perspective, the CM holds several core functions: planning, organizing, directing, controlling, and evaluating the physical execution of construction works, in accordance with contractual deadlines, specifications, and established budgets. Consequently, CMs ensure that every task is executed efficiently by coordinating activities, resources, equipment, and information. The typical organizational structure of a top-tier construction company (contractor) is a pyramidal hierarchy, where each CM is accountable to a supervisor, who in turn reports to the Director. It is well-known that the CM is a professional figure with a dual role: as a leader to their team and as a subordinate to the construction company’s management. This paper focuses on the CM as a ‘leader’ within their entrusted functions, setting aside the perspective of the CM as a subordinate within the contracting firm.

2.2. Conceptualizing Leadership Within the Construction Industry

For more than five decades, leadership has remained a central axis of research in the scientific literature. Due to the multiplicity of perspectives from which it is examined, the definitions and dimensions of this phenomenon are as varied as they are complex. Broadly speaking, the theoretical framework of leadership seeks to classify the figure of the leader, examine the mechanism of influence exerted over followers, evaluate the goals shared by team members, and analyze the motivational methods employed to optimize productive efficiency, among other aspects. As is well known, the number of conceptualizations of the term is as vast as the number of authors who have attempted to define it [4].
Below, several contemporary contributions that enrich the understanding of this concept are highlighted:
Non-coercive influence process: Leadership is conceived as a complex phenomenon with repercussions on organizational, social, and personal dynamics. It depends on an influence process that inspires individuals to work toward collective goals through intrinsic motivation and not through coercion [5].
Competitiveness and performance: It must be understood as the capacity to structure and sustain a human group with high performance relative to its competitors [6].
Joint effort and coordination: It represents the process of driving people to collaborate jointly to achieve great things [7]. In this sense, leaders are those individuals capable of guiding contributions toward group objectives and coordinating their achievement [8].
Facilitation and understanding: It is defined as the action of influencing others to achieve a consensus on what to do and how to execute it, facilitating individual and collective efforts in pursuit of common goals [9].
Systemic bond and authority: It constitutes a type of interpersonal bond manifested in multiple ways within a system [10], characterized by the ability of an individual to influence another in order to achieve specific goals [11]. Problem-solving: Finally, its value is highlighted as a key tool that fosters the resolution of complex problems [12]. Consequently, leadership lacks a unified and stable definition, establishing itself instead as a dynamic, complex, and constantly evolving process [13].
An effective perspective for understanding leadership is to analyze it as a continuous process. Under this approach, the behaviors of managers in the field of building construction have been examined by [14], whose work concludes that it is indispensable to consolidate a comprehensive leadership culture that incorporates training and development programs as critical factors for success. For their part, [15] argue for the need to strengthen the leadership agenda in construction, moving beyond the traditional mindset based on transactions and tasks of sector professionals to prioritize interpersonal skills and soft skills.
Managing behavior and human relations represents an inescapable challenge for any leader. The scientific literature offers a wide spectrum of theoretical approaches that classify leadership styles. The fundamental value of a leader lies in their role as a driver and catalyst of added value for the organization [16].
Within the construction sector, research has been developed based on the leadership models of Burns [17] and from the perspective of [18], where the adopted style is contingent upon the influence the leader exerts over their collaborators to achieve the established performance or objectives. In this way, two main approaches are distinguished:
Transformational Leadership: Composed of four fundamental dimensions: influence, motivation, intellectual stimulation, and individualized consideration of responsibilities toward subordinates. In this modality, the achievement of objectives is not linked to explicit rewards.
Transactional Leadership: Unlike the former, the leader implements a system of incentives or rewards in exchange for followers meeting the proposed goals.
In this regard, ref. [19] found that construction professionals resort to transformational leadership more frequently than transactional leadership. However, despite the existing literature on management and leadership in construction, there is still no direct evidence regarding the application of effective leadership competencies within the profile of the Construction Manager (CM) inside the Spanish sector.
Theoretical Approaches and Typologies of Leadership: Among the theoretical frameworks that evaluate the qualities of a leader, leader trait theory and behavioral theory stand out. Trait theory [20] maintains that leadership capacities are innate; in contrast, behavioral theory [21] focuses on analyzing the behaviors of leaders and their correlation with effective leadership—an inherently complex concept.
For the purposes of this article, the analysis will focus on the leadership styles applied to the study of the CM’s behavior in the construction industry. From the behavioral perspective, leaders can be grouped into three typologies according to the use they make of their authority [22]. Supporting themselves with trait theory, the particularities of each style are briefly defined. From this point of view, ref. [23] examines three profiles: democratic, autocratic, and liberal. This approach is adopted in the present research because it is considered the most appropriate for classifying the leadership style assumed by the CM in their professional practice in relation to the rest of the involved agents (owners, project managers, subcontractors, suppliers, clients, etc.).
The main characteristics of each style are summarized below:
  • Autocratic Leader (AL): An individual who imposes guidelines and demands strict compliance; they are dogmatic, self-confident, and manage the team through the ability to grant or withhold incentives and sanctions [24,25].
  • Democratic/Participative Leadership (PL): Consults subordinates regarding the decisions and actions to be taken, encouraging their active intervention without centralizing power in their person [26].
  • Laissez-faire/Liberal Leader (LL): Exercises minimal use of their authority, granting employees a high margin of autonomy under the premise that they will make the best decisions possible; this type of leader provides full backing to their followers, expecting them to meet the established goals [24].
The Impact of Participative Leadership on Conflict Management: This study posits that participative leadership is the only style with a real influence on dispute resolution capacity [19]. In line with the perspective of [27], it is suggested that the participative approach favors constructive controversy. This methodology allows on-site discrepancies to be transformed into learning opportunities, unlike autocratic or liberal styles, which usually lead to avoidance or imposition, thereby limiting the effective resolution of conflicts. Consequently, participative leadership is defined as the process of distributing decision-making power between higher levels and subordinates [28]. In the construction environment, this model breaks away from the conventional “command and control” hierarchical structure.
The validity of this approach is solidly backed by various findings within the sector’s literature. On the one hand, the participative system has been classified as the most efficient mechanism to boost productivity [29], while also demonstrating that the active intervention of collaborators enhances project quality [30]. In highly uncertain environments, this leadership style stimulates commitment [31] and, specifically within the construction sector, mitigates contractual misunderstandings [32] while consolidating high-performance work teams [33]. Furthermore, modern construction demands leaders capable of actively integrating subcontractors [34], given that project success is directly conditioned by the Construction Manager’s (CM) leadership style [35]. Finally, participation has been proven to increase loyalty and commitment on-site [36], positioning itself as the approach that best adapts to the intrinsic complexity of civil engineering projects [37].

2.3. Work Motivation of the CM

The motivation of construction workers has been a widely studied topic in the literature. There is a consensus that motivation significantly affects worker productivity within the construction industry [38]. The study conducted by [39] analyzed the impact of various organizational factors (effectiveness, openness, cohesiveness, and goal clarity and difficulty) on employee motivation, performance, and job satisfaction. These authors concluded that contractors must effectively manage their work teams through planning, organization, staffing, direction, and control to improve both performance and worker satisfaction. Other research analyzing motivational factors affecting employee performance suggests that the most critical factors are job security, followed by salary and promotion arrangements; conversely, taking on responsibility was found to be the least motivating factor for workers [40]. Motivation is the psychological construct that drives persistent effort toward project objectives [41].
In the construction industry, employee motivation possesses distinct characteristics dictated by the nature of the projects themselves: high volatility, physically taxing environments, substantial occupational risks, and a structural framework rooted in subcontracting. Synthesizing this body of specialized literature, the CM’s work motivation within this research is conceptualized as follows: ‘The psychological state and readiness of the CM to direct their efforts toward project milestones—namely quality, schedule, and budget constraints—propelled by a synergy of intrinsic motivators (recognition, pride in workmanship) and extrinsic incentives (compensation, job security, and on-site working conditions)’ (Adapted [39]).
For a CM, motivation is not merely salary-based; it is also intrinsic and achievement-oriented. Conceptualizations of motivation range from foundational psychological models to project-specific applications. For instance, safety and self-actualization on construction sites are often rooted in the hierarchy of needs theory [42], alongside the distinction between hygiene factors and motivators introduced by [41]. Intrinsic motivation has been heavily framed around Self-Determination Theory [43] and the leverage of job design and autonomy [44]. When applied to project execution, team-level motivation acts as a critical success factor [45], though it is constantly threatened by site-related stress [46]. This intrinsic drive not only fuels creative problem-solving [47] but is also shaped by balanced financial and non-financial incentives [48]. Ultimately, modern literature treats motivation as a shifting variable, fluctuating across project stages [49] and deeply influencing psychological decision-making under intense pressure [50].

2.4. Conflict Resolution Capacity

The construction industry is characterized by fragmentation, uncertainty, and the interdependence of multiple stakeholders, making construction sites environments prone to conflict. For a CM, conflict resolution capacity is not merely a skill, but a critical technical and human competency that directly impacts the project schedule and cost. The recent literature defines site conflict not only as a legal dispute but as an incompatibility of goals or values among site actors—such as subcontractors, suppliers, and the project management team—requiring continuous management [51]. For a CM, possessing conflict resolution capacity—defined by the ability to deploy integrating, avoiding, compromising, dominating, and obliging strategies [52]—is indispensable. Research on this topic spans from foundational taxonomies of conflict-handling styles [53] and early construction-specific studies [54] to behavioral analyses during project crises [55]. Pinpointing the triggers, ref. [51] categorized design, payments, and communication as the primary catalysts of construction disputes. Mitigating these issues often hinges on relational dynamics; trust between partners has been shown to drive integrative resolutions [56], preventing the heavy economic toll associated with unresolved conflicts in major infrastructure works [57]. Consequently, contemporary research focuses on proactive solutions, offering systemic prevention models for job sites [58] and meta-analytical insights into how task and relationship conflicts differentially affect project performance [59].

3. Conceptual Model and Hypotheses Development

Participative Leadership to Conflict Resolution: Participative leadership reduces information asymmetry. By involving all parties, the participative leader fosters an ‘integrating’ style [60]. The literature suggests that participation builds a foundation of trust that allows technical disputes to be resolved without resorting to litigation [61].
Participative Leadership to Motivation: According to Self-Determination Theory [62], autonomy and participation are basic nutrients of intrinsic motivation. A CM who feels their voice matters feels more competent and more closely linked to the project’s success.
Work Motivation to Conflict Resolution Capacity: Conflict resolution demands high cognitive and emotional energy expenditure. A motivated individual possesses greater ‘absorptive capacity’ and resilience to negotiate under pressure [47]. Motivation acts as the necessary fuel to persist in the pursuit of ‘win–win’ solutions. On this basis, the research model is shown in Figure 1, and thus, the following hypothesis is proposed:
Hypothesis 1 (H1).
Participative Leadership has a positive and direct effect on the Work Motivation of Construction Managers.
Hypothesis 2 (H2).
Participative Leadership has a positive and direct effect on the Conflict Resolution Capacity of Construction Managers.
Hypothesis 3 (H3).
Work motivation positively mediates the relationship between Participative Leadership and Conflict Resolution Capacity of Construction Managers.

4. Methodology and Data Analysis

4.1. Methodological Diagnostics: Non-Response Bias and Common Method Bias

To ensure the robustness and generalizability of the empirical findings, two preliminary analyses were conducted: non-response bias and common method bias (CMB). First, non-response bias was evaluated using the time-trend extrapolation method, which compares early respondents (those who completed the survey in the first waves) with late respondents (representing the proxy for non-respondents). Independent sample t-tests were executed on key demographic indicators, such as Construction Manager experience and firm size. The results indicated no statistically significant differences between the two groups (p > 0.05), confirming that non-response bias does not affect the validity of the data.
Second, because the data were self-reported and collected from a single source (the Construction Managers), common method bias could potentially distort the examined relationships. To address this, a full collinearity assessment approach was conducted using SmartPLS 4, as strongly recommended for variance-based structural equation modeling. This method requires that all inner Variance Inflation Factors (VIF) obtained through a full collinearity test remain below the strict threshold of 3.3. As displayed in the measurement model assessment, the maximum VIF value obtained in this study was 2.905 (for the WM2 indicator), staying comfortably below the 3.3 critical limit. Consequently, it can be confidently asserted that common method bias is not a pervasive threat to this research.

4.2. Research Method

The target population of this study consists of CM from construction companies (contractors). To obtain the data, a survey was designed that included company information as well as questions related to the model’s main variables. The questionnaire was reviewed by academic experts, and subsequently, a pilot study was conducted with five construction managers. A total of 118 correctly completed questionnaires were validated. Professional associations of architects and engineers in Spain assisted in distributing the survey to those in charge of construction sites by sending the questionnaire directly to their personal email addresses via a link (URL). This study was conducted ensuring compliance with ethical standards. At the beginning of the survey, all participants were provided with an informed consent form detailing the objectives of the study and ensuring that participation was strictly voluntary. To guarantee confidentiality, the process of data collection and processing was conducted under strict anonymity, in rigorous compliance with current data protection regulations, including the General Data Protection Regulation (GDPR). Finally, respondents were assured that the data obtained would be processed and analyzed exclusively in an aggregated and statistical manner, preventing the individual identification of subjects or their respective companies. Fieldwork was carried out between November 2022 and September 2023; 123 surveys were received, and 118 were validated, as some were not completed correctly. The final sample consisted of 118 active CM. The sample size (n = 118) is considered adequate for the requirements of PLS-SEM. According to [63] power analysis and the guidelines established by [64], for a model with six predictors and a target statistical power of 0.80, the minimum threshold to detect effects with an f2 of 0.15 is 98 cases (using the GPowerNT software, version 3.1.9.7). Given that the current sample of 118 active project managers exceeds this threshold, the model is sufficiently robust to detect statistically significant relationships with a 95% confidence level. For data analysis and the testing of the proposed hypotheses, Partial Least Squares Structural Equation Modeling (PLS-SEM) was chosen. This decision is based on several critical reasons aligned with the research objectives. First, PLS-SEM is a prediction-oriented technique, ideal for studies seeking to identify determinant constructs in a complex phenomenon, such as conflict resolution capacity. Second, this methodology offers greater statistical flexibility by not requiring the fulfillment of distributional normality assumptions, a common situation in surveys of construction industry professionals. Furthermore, PLS-SEM is highly effective in handling small sample sizes (n = 118) and models with multiple mediating variables, offering greater statistical power than Covariance-Based Structural Equation Modeling (CB-SEM) under these conditions. The choice of PLS-SEM is based on its ability to offer greater statistical power in samples that do not meet the levels required by CB-SEM. Furthermore, its non-parametric nature makes it highly robust in the face of non-normal data distributions. Finally, given that this study employs formative constructs for predictive-exploratory purposes, this methodology is superior for maximizing the explained variance of conflict resolution capacity.
The rationale for choosing PLS-SEM over CB-SEM is fundamentally driven by the unique characteristics of our sample and data distribution. First, while CB-SEM demands large samples (n > 200) to guarantee stable parameter estimations and avoid non-convergence issues, our final sample consists of 118 active CM. Although this sample size is robust and highly representative for PLS-SEM—exceeding the required threshold (n = 98) to achieve a statistical power of 0.80—it falls short for the strict requirements of CB-SEM. Second, a rigorous assessment of data normality through the Shapiro–Wilk test revealed significant non-normal distributions across several Likert-scale indicators. CB-SEM relies heavily on the assumption of multivariate normality, and violating this condition severely biases chi-square goodness-of-fit statistics and inflates Type I errors. In contrast, PLS-SEM is a non-parametric method that does not require distributional assumptions, offering substantially higher statistical power and parameter stability when handling non-normal data in small-to-medium sample sizes.

5. Result and Discussion

The descriptive statistics of the sampled companies are presented in Table 1.
Based on the literature review, the questions defining the model variables were established: Participative Leadership (PL), Work Motivation (WM) and Conflict Resolution Skills (CRS). All indicators (items) were evaluated using a 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). The questions related to the model variables were designed based on the literature and adapted by the researchers as shown in Table 2. In PLS-SEM, the evaluation of the global model fit must be performed first [65]: (i) the standardized root mean square residual (SRMR) of the global model; (ii) the unweighted least squares discrepancy (d_ULS); and (iii) the geodesic discrepancy (d_G).
Table 3 shows the values obtained for the model fit. Subsequently, the evaluation of both the measurement model and the structural model was carried out. PLS is a variance-based structural modeling technique that models and links concepts like latent variables or constructs addressed through indicators or manifest variables [66]. This technique was chosen because the variables underlying the conceptual model are modeled as formative constructs. That is, each variable is measured by indicators that capture different aspects of the variable to be measured. The use of PLS is recommended when supporting a formative measurement model [67,68,69,70]. Furthermore, this work emphasizes the prediction of dependent variables [71]. Additionally, SmartPLS 4 software [72] was used, a world-renowned software for data analysis using the PLS-SEM method. Regarding the measurement model, since all constructs are formative, it is necessary to verify the indicator weights and the Variance Inflation Factor (VIF). The VIF value must be below 3.3 [73] to eliminate potential collinearity between indicators.
Regarding the structural model, the statistical significance of the relationships between constructs is evaluated using Path coefficients and their T-values. As predictive values, the coefficient of determination (R2) of the explanatory model or dependent variable (CRC) is assessed. R2 indicates the amount of variance in a construct explained by the predictor variables of the endogenous construct, with values ranging from zero to one. The higher the R2 value, the greater the predictive power.
Table 4 shows the values obtained for the measurement model. The negative weight observed for indicator WM1 was analyzed under multicollinearity criteria. Given that the Variance Inflation Factor (VIF) was below 3.3 and its absolute outer loading was significant, the indicator was retained, interpreting it as an inverse contribution to the formation of the construct. As can be observed, the control variables (Construction Manager’s experience, age, and gender) do not have a significant effect on conflict resolution capacity.
Table 5 shows the values obtained for the structural model. The results reveal a significant direct effect of participative leadership on conflict resolution (β = 0.675). Furthermore, a complementary partial mediation through motivation was confirmed (β = 0.196; VAF = 22.5%). The model demonstrates strong predictive power (R2 = 0.525) and an optimal global fit (SRMR = 0.062).
A one-tailed test was chosen because the proposed hypotheses are directional, grounded in the previous literature that establishes a positive relationship between motivation and conflict resolution effectiveness.
The study conducted by [74] recommend values of 0.75, 0.50, and 0.25 as substantial, moderate, and weak, respectively. In the structural model, R2 = 0.525 obtained a ‘moderate’ value for ‘CRC’, implying that PL and WM explain 52.5% of the variance for the CRC. In the construction industry, as predicted by the literature, flexible leadership styles enhance performance by reducing stress and improving well-being at work. Participative leadership does not improve conflict resolution spontaneously; rather, it does so because it first increases the Construction Manager’s motivation, and it is precisely this motivation that ultimately provides the energy or willingness to resolve conflicts successfully.
The calculated Variance Accounted For (VAF = 22.5%) establishes that Work Motivation (WM) acts as a complementary partial mediator in the model. This value aligns with and confirms findings in the contemporary construction management literature. For instance, in wider organizational psychology frameworks analyzing adaptive competencies under pressure, intrinsic motivational constructs typically account for approximately 20–25% of the indirect variance of leadership impacts. This cross-study consistency demonstrates that while participative leadership directly drives the strategic and structural mechanics of dispute resolution (77.5% of the effect), the psychological commitment ignited by motivation supplies the critical engine that optimizes the outcome.
The Mediating Effect (VAF = 22.5%): This mediation is justified because leadership is not merely a mechanical work structure, but a process of human influence. While PL improves CRC directly through procedural means, it also acts indirectly by ‘igniting’ the CM’s psychological commitment (motivation). This internal drive, in turn, renders the CM more effective at the negotiating table.
These results are highly significant as they demonstrate that, while participative leadership is powerful on its own, overlooking motivation would result in losing nearly a quarter of the effectiveness in conflict resolution. The model predicts that PL and WM jointly explain 52.5% of the variance in CRC, representing a moderately strong predictive effect for the construction sector. Furthermore, the model fit was validated using the SRMR indicator, which yielded a value of 0.062. As this is below the critical threshold of 0.08, it confirms that the proposed model is a reliable and statistically valid representation of the observed empirical relationship. The majority of the total effect (77.50%) remains direct (c’ = 0.675). This signifies that, although direct management is the dominant factor, the mediation of WM provides critical added value to achieve the reported efficiency levels. The mediating construct WM presents an R2 of 0.363 with a p-value = 0.000, which validates its statistical relevance within the structural model. The model confirms that the CM’s WM acts as a key partial mediator (VAF = 22.50%) between leadership and problem-solving. This implies that the participative style does not only resolve conflicts through its methodology, but also by increasing the Motivation of the CM themselves, which explains nearly a quarter of the variance in resolution efficiency. For construction companies, this suggests that a motivated leader is substantially more decisive when facing on-site crises.

IPMA (Importance–Performance Map Analysis)

IPMA was conducted using CRC as the target variable. The results reveal that PL is the most relevant predictor. For its part, MW showed moderate importance. In contrast, the control variables related to the construction manager’s profile experience, age, and gender exhibited negligible total effects on CRC. These data suggest that effective conflict resolution is not a skill acquired passively through time or seniority; rather, it depends directly on the management competencies and the participative approach that the professional chooses to implement. Data analysis and calculations were performed using SmartPLS 4 software.
Table 6 shows the values obtained for IPMA. Through the IPMA, it is identified that PL is not only the most important variable but also the one with the highest current performance (82.73). In contrast, WM, while showing solid performance (77.78), possesses a margin for improvement that could significantly boost the Construction Manager’s overall CRC effectiveness. As shown in Figure 2, the Importance–Performance Matrix Analysis (IPMA) illustrates the prioritization of constructs based on their total effects and performance scores. The results reveal that the LP construct is the most relevant factor for the model, presenting both the highest importance (0.673) and the highest performance (82.73). This suggests that the current strategies associated with LP are highly effective and constitute the foundation of the RDC performance.
From a management perspective, the IPMA indicates that to enhance the RDC variable, efforts should continue to prioritize the strengthening of LP, given its high impact. However, noting that ML shows lower performance than LP despite having significant importance, there is a margin for improvement in ML that could result in a direct increase in the overall efficiency of the model. Demographic variables (Age, Gender, Experience), due to their low importance, are not considered critical leverage points for improving the results of the target construct.
This study also applied the same model to autocratic and laissez-faire leadership styles. Consistent with the existing literature, these leadership styles lacked statistical significance regarding conflict resolution capacity; however, the construction manager’s work motivation remained a significant factor in both models.

6. Conclusions

In the construction industry, conflict resolution is not merely a situational fix but a critical process of capturing and externalizing tacit knowledge. Therefore, construction firms must ensure that the insights gained from conflict resolution are transferred and embedded into the firm’s knowledge management systems to prevent future friction and improve competitive advantages. Theoretically, we have enhanced the debate on how participative leadership acts as a catalyst that triggers intrinsic psychological drivers (motivation), which in turn enables adaptive behavioral capabilities (conflict resolution). Practically, we have formulated precise recommendations for HR managers in construction firms, emphasizing the design of leadership development programs and specific corporate training frameworks focused on participatory communication as a tool to mitigate project overruns and stakeholder friction. Assuming that a CM possesses training consistent with the type of project they oversee, this study demonstrates that construction firms must foster training in work motivation and participative leadership to enhance the project manager’s conflict resolution capabilities beyond factors such as experience. The CM performs a highly complex, hybrid managerial role within the construction company. As a technical and operational representative, they act as a coordination node between multiple external agents (subcontractors, suppliers, and clients) and the internal hierarchical structure. This position of “strategic subordination” implies a critical duality: the project manager must exercise autonomous leadership in managing resources on-site while maintaining a direct dependence on senior management, to whom they are accountable for performance indicators summarized as Time, Cost, Quality, Safety, and Sustainability. Furthermore, as predicted by the literature, leadership style influences the managerial skills required to successfully lead large and diverse teams. This work demonstrates that a democratic-participative leadership style is key, as it generates a sense of commitment among the various construction agents on-site. As is well known, leadership can shift according to particular or special situations. To maintain stable and consistent research results, project managers were asked to complete the questionnaire based on their daily routines rather than special circumstances. A limitation of this study is its cross-sectional design; a longitudinal analysis should be considered, reviewing the proposed model on an annual basis. Therefore, due to the exploratory nature of the study, the results should not be generalized to the national level (Spain); rather, they should be analyzed solely in the context of the participants (118). Future research should shed light on this issue. This study contributes to construction management best practices and demonstrates that motivation influences a project manager’s conflict resolution abilities. A motivated Project Manager who also motivates their team develops Emotional Intelligence. This ensures that when conflict arises—which is inevitable on-site—a participative leader addresses it through collaboration rather than confrontation. Without motivation, the Project Manager typically resolves conflicts through imposition or authority, which generates resentment and further long-term issues across the chain of subordinates, collaborators, suppliers, and subcontractors. In organizational psychology, a motivated leader feels capable of facing both technical and human disputes. As a limitation of this study, the results cannot be extrapolated to other countries. The construction sector in Spain presents a traditionally hierarchical structure that prioritizes immediate economic margins over human capital management. This organizational culture creates hostile work environments that inhibit collaboration, transforming the human factor into an underutilized variable. The results of this study suggest that this rigid hierarchization is counterproductive, as the disregard for human relationships increases indirect costs derived from conflict and operational inefficiency. Therefore, a high level of work motivation combined with participative leadership in the Project Manager increases the efficiency and quality of conflict resolution strategies. If the knowledge of how to resolve a technical issue or a complex negotiation resides solely in CM’s head, the organization is vulnerable. If that person leaves, the capacity for resolution is lost. By codifying that knowledge (converting it into explicit knowledge through best-practice guides, incident databases, action protocols, and dispute resolution templates), the company standardizes its response capacity. The project team does not have to “reinvent the wheel” every time a conflict arises with a subcontractor or the site management. These findings demand a redefinition of professional profiles in the construction sector, where technical competence must be complemented by leadership and motivational competencies. Future studies should perform a multi-group analysis (MGA) to compare the model’s paths based on the gender of the CPM. Finally, future works should replicate the study with broader, multi-regional samples.

Author Contributions

Conceptualization, M.V.M.; methodology, M.V.M.; software, M.V.M.; validation, M.V.M. and F.V.M.; research, M.V.M.; resources, M.V.M.; data curation, M.V.M. and F.V.M.; drafting, review and editing, M.V.M. and F.V.M.; supervision, F.V.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

According to institutional regulations, formal approval from the Research Ethics Committee of the UCAM was not required for this specific study.

Informed Consent Statement

All participants were fully informed about the aim of the study, how the data would be used for academic purposes, and explicitly gave their consent before completing the questionnaire.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors upon reasonable request.

Acknowledgments

Many thanks to the following professional associations for their cooperation: CITOP Spain (Institute of Technical Engineers in Civil Engineering), CICCP Andalusia (Institute of Civil Engineers) and CEACOP (Association of Andalusian Companies in Construction, Consulting, and Public Works).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
WMWork Motivation
PLParticipative Leadership
CRCConflict Resolution Capacity
EXPExperience
AGEAge
GENGender

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Buildings 16 02471 g001
Figure 1. Conceptual Model and Hypotheses.
Figure 1. Conceptual Model and Hypotheses.
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Buildings 16 02471 g002
Figure 2. Importance Performance Matrix Analysis (IPMA) results for Conflict Resolution Capacity.
Figure 2. Importance Performance Matrix Analysis (IPMA) results for Conflict Resolution Capacity.
Buildings 16 02471 g002
Table 1. Descriptive statistics of the sample.
Table 1. Descriptive statistics of the sample.
CM (n = 118)
Man: 87.2%Woman: 12.8%
Age CM 25–29 years (12%)30–49 (65%)50–65 (23%)
Contractor Age<30 years: 27%
31–50 years: 39%
>50 years: 34%
CM QualificationsEngineering 78%Architecture 22%
Infrastructure TypologyCivil Engineering 79%
Building Construction 16%
Industrial Construction 5%
Industrial 5%
CM Experience(1–5 years): 25%
(6–10 years): 28%
(11–20 years): 30%
>20 years: 17%
BIM technology is used in the construction phase92.3% No 7.7% Yes (1–3 years)
Contractor size11–50: 20.7%
51–250: 31%
More than 250: 48.3%
Field of ActivityNational 68.8% International 30.2%
ISO 9001 CertificationYes (88.8%) No (11.20%)
ISO 14001 CertificationYes (88.9%) No (11.10%)
OHSAS 18001 CertificationYes (84.6%) No (15.40%)
Annual Turnover<2 Million euros: 8%
Between 2–10 Million Euros: 9.5%
Between 11–50 Million Euros: 17%
50 Million euros > €: 45.5%
% Public Sector Contracts (last 3 years)<20%: 21.1%
Between 20–40%: 10.5%
Between 40–60%: 24.6%
>80%: 43.9%
Table 2. Survey Items.
Table 2. Survey Items.
ConstructsItemsIndicators Adapted from the Literature
Work Motivation
(WM)		WM1The idea of working every day as a construction manager in your job motivates you.[38,39,40]
WM2You derive personal satisfaction from your job duties.
WM3To achieve the established goals, as a construction manager, you foster motivation among your team members.
WM4Serving as a site manager brings you personal and professional achievement, irrespective of the day-to-day challenges on-site.
Participative Leadership
(PL)		PL1Foster teamwork and personal relationships to achieve peak performance.[4,5,26]
PL2Communication is a key factor among team members.
PL3Responsibility is shared with subordinates by consulting them and including them in the decision-making team.
PL4Participation is an important factor among team members.
Conflict Resolution Capacity (CRC)CRS1To resolve conflicts during infrastructure execution (technical or quality-related), you, as the Site Manager, propose alternative solutions that improve upon the original project design.[51,52,53]
CRS2In the event of a financial conflict (project losses), the outcome is improved by submitting new claims or change orders to the Project Management.
CRS3When a conflict arises between members of my team, I always try to resolve it.
CRS4I believe that my clients are satisfied with the way I resolve conflicts that arise during the execution of works or infrastructure.
Control Variables
ExperienceEXPYears of experience as a CM
AgeAGEage of the CM
GenderGENgender of the CM
Table 3. Model fit.
Table 3. Model fit.
Estimated ValueSuggested Threshold
SRMR0.065<0.080God fit
d_ULS0.509<95% HIOptimal
d_G0.181<95% HIOptimal
Table 4. Measurement model.
Table 4. Measurement model.
ItemsWeightVIF5.0%95.0%
PLPL10.576 ***1.5010.3670.778
PL20.185 n.s.1.515−0.0970.445
PL30.200 *1.3230.0220.384
PL40.332 **1.6650.0900.550
WMWM1−0.338 *2.484−0.646−0.007
WM20.627 **2.9050.2190.958
WM30.642 ***1.2940.4580.791
WM40.180 n.s.1.512−0.0940.452
CRCCRC10.234 n.s.1.147−0.0150.544
CRC2−0.102 n.s.1.081−0.3450.126
CRC30.627 ***1.2120.3770.780
CRC40.482 ***1.2080.2690.618
EXP1.0001.0001.0001.000
AGE1.0001.0001.0001.000
GEN1.0001.0001.0001.000
Note: * p < 0.05; ** p < 0.01; *** p < 0.001 (one-tailed test) n.s.: not significant.
Table 5. Structural Model Results.
Table 5. Structural Model Results.
PathCoeficient (β)/T-ValorImpactHipothesis Testing
H1: PL → MW0.603 ***/10.651Strong/PositiveH1 is Confirmed:
H2: PL → CRC0.477 ***/5.278Moderate/PositiveH2 is Confirmed:
MW → CRC0.325 ***/3.355Positive
Variables de control
EXP → CRC0.019 n.s./0.170Negligible
AGE→ CRC0.014 n.s./0.014Negligible
GEN → CRC−0.037 n.s./0.223Weak/Negative
R2 (CRC) = 0.525 (52.5%) R2 (MW) = 0.363 (36.3%)
H3: PL → MW → RDC Mediation Hypothesis
Effect of the predictor on the mediator: 0.603 (a)
Effect of the mediator on CRC: 0.325 (b)
Direct effect: 0.675 (c’)
Variance Accounted Forà VAF = (a × b)/(a × b + c’) = 0.2250 VAF = 22.50%
0.20 < VAF < 0.80
The Hypothesis H3 is Confirmed: There is Partial Mediation
Bootstrapping (n = 10,000 Sub-samples) *** p < 0.001, n.s.: not significant; t (0.05; 9999) = 1.645; t (0.01; 9999) = 2.327; t (0.001; 9999) = 3.092.
Table 6. IPMA Results.
Table 6. IPMA Results.
ConstructImportance (Total Effects)Performance (0–100)
PL0.67382.73
WM0.32577.78
Age0.01443.55
Exp0.01929.64
Gen−0.03713.56
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Manzanares, M.V.; Manzanares, F.V. Factors Affecting Conflict Resolution Capacity: An Organizational Perspective from Construction Firms. Buildings 2026, 16, 2471. https://doi.org/10.3390/buildings16122471

AMA Style

Manzanares MV, Manzanares FV. Factors Affecting Conflict Resolution Capacity: An Organizational Perspective from Construction Firms. Buildings. 2026; 16(12):2471. https://doi.org/10.3390/buildings16122471

Chicago/Turabian Style

Manzanares, Marcelo Villena, and Francisco Villena Manzanares. 2026. "Factors Affecting Conflict Resolution Capacity: An Organizational Perspective from Construction Firms" Buildings 16, no. 12: 2471. https://doi.org/10.3390/buildings16122471

APA Style

Manzanares, M. V., & Manzanares, F. V. (2026). Factors Affecting Conflict Resolution Capacity: An Organizational Perspective from Construction Firms. Buildings, 16(12), 2471. https://doi.org/10.3390/buildings16122471

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