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Article

The Influence Mechanism of Organizational Context and Tacit Knowledge Sharing on Innovation Performance in Mega Projects

by
Hongsheng Kan
1,2,
Yujuan Li
1,* and
Xue Li
1
1
School of Management Engineering, Qingdao University of Technology, Qingdao 266525, China
2
Research Center for Smart City Construction and Management, Qingdao University of Technology, Qingdao 266520, China
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(17), 3237; https://doi.org/10.3390/buildings15173237
Submission received: 11 August 2025 / Revised: 4 September 2025 / Accepted: 5 September 2025 / Published: 8 September 2025
(This article belongs to the Special Issue Innovation in Construction and Project Management: Digital Technologies, Intelligent Systems, and Sustainable Solutions)
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Abstract

Improving the innovation performance of mega projects has become a central concern in both engineering project management theory and practice. Organizational structure and culture are key contextual factors that can facilitate tacit knowledge sharing across organizations, thereby enhancing innovation outcomes. Based on the data of 243 questionnaires, this paper systematically analyzes the influence mechanism of organizational context factors on innovation performance by using the structural equation model (SEM). The results show that organizational structure exerts a significant negative effect on both tacit knowledge sharing and innovation performance. Among the dimensions of organizational culture, trust climate and organizational support have significant positive effects on both tacit knowledge sharing and innovation performance. While the level of cooperation enhances tacit knowledge sharing, its direct impact on innovation performance is not statistically significant. Furthermore, in the organizational context and innovation performance, tacit knowledge sharing also plays different mediating roles. The results can provide theoretical guidance for mega projects to break through the obstacle of technological transformation and enhance innovation efficiency.

1. Introduction

Under the background of accelerated knowledge iteration in the digital era, mega projects serve as key drivers in the construction of the national infrastructure system and the optimization of the industrial structure. The improvement of their implementation efficiency and innovation performance has become one of the core driving forces for achieving high-quality economic and social development. Compared with conventional construction projects, mega projects involve greater investment scales, more complex technical requirements, and a broader range of stakeholders [1], making them a vital component of China’s modern engineering system. However, these characteristics also expose complex engineering projects to technological, managerial, financial, and market risks [2]. Precisely because of such high levels of risk and uncertainty, project organizations need to foster a favorable organizational context to promote the sharing of tacit knowledge among members, thereby mitigating risks, addressing problems, and ultimately enhancing both innovation performance and the likelihood of project success. Therefore, establishing a systematic innovation-driven mechanism is critical not only for optimizing the effectiveness of full life-cycle project management, but also for facilitating the digital transformation and sustainable development of the construction industry.
The innovative performance of mega projects not only relies on technological breakthroughs but also depends on the organization’s ability to coordinate dynamic organizational contexts and the efficiency of tacit knowledge sharing and transformation. The resource-based theory posits that the rational allocation and utilization of resources enables organizations to establish sustainable competitive advantages [3]. Knowledge resources, as a fundamental means of acquiring and leveraging organizational assets, constitute an indispensable foundation for project innovation [4]. Polanyi [5] first classified knowledge into tacit and explicit forms. Tacit knowledge, which originates from long-term practical experience, is characterized by specificity and practicality. People often absorb and apply tacit knowledge unconsciously and passively, making it difficult to articulate clearly to others. Moreover, tacit knowledge can only be effectively shared through interactive communication and practical engagement. Tacit knowledge is widely recognized as a critical resource for strategic innovation and a foundation for establishing sustainable competitive advantage. Compared with explicit knowledge, tacit knowledge relies more heavily on experiential exchange and socialization processes, which render its transfer more challenging. Consequently, tacit knowledge sharing is not only a core component of knowledge management but also an essential mechanism for strengthening organizational innovation capability. Recent empirical studies consistently emphasize the pivotal role of knowledge sharing in driving innovation performance. At the macro level, knowledge-based dynamic capabilities (KBDCs) foster innovation through knowledge creation, diffusion, absorption, and application. Knowledge creation is the strongest predictor of innovation performance in developed and developing economies, whereas knowledge absorption exerts the greatest influence in transitional economies, underscoring the importance of knowledge-related capabilities [6]. At the firm level, management innovation—encompassing new structures, processes, and practices—significantly enhances innovation outcomes in SMEs. External knowledge search breadth acts as a partial mediator, highlighting the critical role of knowledge acquisition and sharing mechanisms [7]. Similarly, digital transformation directly fosters green technological innovation performance and additionally exerts a mediating effect through internal knowledge sharing [8]. At the project level, digital capability of project teams positively influences innovation performance, with value co-creation serving as a mediator fundamentally dependent on intra- and inter-team knowledge exchange [9]. Overall, across both macro-level innovation ecosystems and micro-level organizational and project practices, knowledge sharing consistently emerges as a central mediator and driver of innovation performance. Nevertheless, although extensive research has examined traditional knowledge management, a comprehensive understanding of tacit knowledge and its linkages with organizational context and innovation performance remains limited. This gap underscores the importance and necessity of further exploring the role of tacit knowledge sharing [10]. Due to their provisionality and the scarcity of sharing environments, individual knowledge and experience generated during the implementation of mega projects stay in the minds of organizational members and are lost with the dissolution of the organization after the completion of the project, leading to increased difficulties in sharing tacit knowledge during the implementation of the project in all phases [11]. Therefore, further elucidating the mechanism of tacit knowledge sharing in linking organizational context with innovation performance is of critical significance for strengthening managerial effectiveness and advancing the innovation capability of complex engineering projects.
With the dynamic evolution of governance mechanisms in mega projects and the ongoing improvement of governance capacity, the organizational context have become increasingly susceptible to the influence of institutional environments, resource constraints, and organizational climate [12]. As a system encompassing deep-seated values and behavioral norms, organizational culture shapes the project team’s cognitive and behavioral patterns toward innovation through contextual embedding. In contrast, organizational structure provides infrastructural support for innovation activities by delineating authority and responsibility, establishing coordination mechanisms, and facilitating information flow. According to social exchange theory, resource interactions among actors can be conceptualized as a form of reciprocal exchange. The core premise of this theory is that relationships among individuals follow the principle of reciprocity, whereby the returns from exchange encompass not only material benefits but also psychological outcomes, including support, trust, and cooperation. Resource exchange can occur through formal contractual arrangements or through interpersonal trust. In recent years, research on organizational context has shifted from focusing on its conceptualization and definitions to examining the mechanisms through which different contextual elements influence innovation and knowledge processes. A review of the existing literature reveals that current studies on organizational context primarily address the following dimensions: in terms of research content, it mainly focuses on the impact of organizational context on knowledge-sharing behavior [13] and knowledge-sharing willingness [14], the impact of organizational context on employees’ and organizations’ performance [15], and the impact of organizational context on organizational learning [16], etc.; in terms of the research object, studies on organizational context mainly concentrate on individual employees [15], small- and medium-sized enterprises, and within business organizations [13]. From a knowledge management perspective, the mechanisms by which the sharing of tacit knowledge affects the organizational environment and innovation performance remain under-researched. This is particularly true in the field of mega projects. Despite a growing academic interest in organizational context and innovation performance under the broader innovation-driven development strategy, existing studies tend to treat organizational context as a single static factor, focusing on enterprise-level environments or generalized effects on knowledge sharing and transfer. There is a notable gap in understanding the deeper mechanisms by which organizational context affects innovation outcomes in large-scale, multi-stakeholder projects, as well as the mediating or moderating role of tacit knowledge sharing in this process.
In summary, investigating the influence of organizational context on innovation performance in mega projects is of substantial value. Such research provides important theoretical and practical insights. These insights are essential for constructing a compatible organizational environment that fosters significant advancements in innovation capability and outcomes. This study develops a mechanism model with tacit knowledge sharing as a mediating variable, systematically analyzes the multidimensional components of organizational context, and proposes a research hypothesis framework structured as “organizational context—tacit knowledge sharing—innovation performance”. In the first phase, hypotheses concerning the effects of organizational context and tacit knowledge sharing on innovation performance were derived from a comprehensive literature review, leading to the construction of a theoretical model. Subsequently, the theoretical model was empirically tested using Structural Equation Modeling (SEM).

2. Literature Review and Hypotheses

2.1. Organizational Context and Innovation Performance

In essence, an organizational context refers to the setting in which members of an organization interact with the external environment. This encompasses fundamental characteristics such as organizational culture, structure, and available resources, along with factors like information technology and individual attributes [17]. However, the organizational context of mega projects diverges significantly from that of conventional corporate entities due to their distinctive features. In particular, mega projects are characterized by a unique distribution of responsibilities and a multidimensional structure.
Given these differences, this paper defines the organizational context of mega projects in the context of multi-party collaborative work, high uncertainty, and long-term dynamic changes; the temporary collaborative system formed around the project goals includes formal structural arrangements and informal cultural atmospheres. Based on the above definition, this paper starts from the applicability of engineering management and draws on Zhou Guohua’s classification of the dimensions of organizational context [14]. It focuses on two core aspects: organizational structure and organizational culture. Among them, organizational structure includes the degree of centralization and formalization, while organizational culture includes trust climate, organizational support, and cooperation level. A situational measurement system that better fits the characteristics of complex engineering projects is constructed to provide a theoretical basis and operational path for subsequent model analysis.

2.1.1. Organizational Structure and Innovation Performance

Mega projects are characterized by multi-party collaboration, dynamics, and high risk, which are closely related to the innovation performance and coordination ability of the organizational structure. Organizational structure affects knowledge flow and decision-making efficiency through the distribution of authority and responsibility, communication mechanism, and integration capability, which in turn affect the output of innovation results. As the carrier of knowledge innovation, the organizational structure provides the necessary internal conditions for knowledge innovation by influencing the efficiency of information and knowledge exchange between individuals. This, in turn, plays a role in the organization’s overall innovation effectiveness. Research has shown that construction project organizations typically adopt integrated structural models and that both their organizational capabilities and structural design have a significant impact on project innovation performance [18]. While highly formalized organizational structures provide advantages in control and coordination, they often create decision-making bottlenecks and impede knowledge sharing, thereby constraining the transformation of innovation outcomes [19]. In contrast, agile organizations emphasize decentralization and cross-functional team collaboration. Their iterative practices not only improve the quality of project team cooperation but also significantly enhance project performance and innovation capability by fostering communication and knowledge sharing [20]. Empirical studies further demonstrate a positive relationship between agile practices and project success, a link that is primarily mediated by improvements in team cooperation quality [21]. Therefore, in the context of mega projects, agile organizational structures can be regarded as an important complement to traditional hierarchical forms. Their flexibility and collaborative orientation not only mitigate innovation barriers associated with structural rigidity but also offer novel governance approaches for enhancing cross-organizational innovation performance. However, there is still no consensus on how specific structural dimensions influence innovation performance in the context of mega projects. While scholars have examined organizational structure from various angles [18,22], the degree of centralization and formalization remains the primary focus of most studies. When power is overly centralized, the exchange of information and knowledge among members will be limited, making it difficult to realize innovation. Innovative activities in mega projects have a high degree of uncertainty, and the strict regulations on members’ rights and responsibilities in highly formalized organization are not conducive to creating a relaxed innovation atmosphere, which in turn inhibits innovative behavior and reduces project innovation performance.
Based on this, the following hypotheses are proposed:
H1: 
Organizational structure has a significant negative effect on innovation performance in mega projects.
H1a: 
Organizational formalization has a significant negative effect on innovation performance in mega projects.
H1b: 
Organizational centralization has a significant negative effect on innovation performance in mega projects.

2.1.2. Organizational Culture and Innovation Performance

Organizational culture combines organizational values with practical behavioral patterns. It serves both as a guiding framework for the management system and as a practical mechanism for reinforcing those values [23]. According to pertinent research, organizational culture is the primary factor influencing organizational innovation. Given the high level of dynamism and uncertainty in the external environment, organizations must continuously refine their cultural systems to remain adaptive. In other words, by updating and restructuring cultural elements, an organization can better stimulate internal innovation and achieve long-term development [24]. Conversely, an unhealthy organizational culture may lead to chronic employee stress and low morale, ultimately hindering the sustainable development of the enterprise [25]. Previous studies have highlighted organizational culture as a key driver of innovation performance. Empirical research grounded in the Competing Values Framework (CVF) demonstrates that organizational culture significantly enhances organizational performance by fostering innovativeness. Moreover, innovation functions as a mediating mechanism between organizational culture and performance, suggesting that culture not only directly shapes employee behaviors but also contributes to performance improvement through the facilitation of innovation processes [26]. Drawing on previous research, this paper identifies three core dimensions of organizational culture: trust climate, organizational support, and level of cooperation [14,17]. The trust climate reflects the degree of open communication and mutual trust among organizational members, which helps reduce the barriers to knowledge sharing; organizational support represents the recognition and incentive mechanism of the organization for members’ innovative behaviors; the cooperation level reflects the intensity of collaborative awareness and team collaboration practices within the organization. These are all key cultural factors that promote knowledge exchange and innovation in mega projects.
In psychology, trust refers to an individual’s evaluation of the reliability and credibility of their environment and the entities they engage with. Over time, academic research on trust has expanded from an initial focus on intra-organizational relationships to include inter-organizational trust across various fields. In highly dynamic and uncertain environments, inter-organizational trust plays a double-edged role: while it can foster cooperation and innovation, it may also lead to dependency or risk if mismanaged. Therefore, choosing an appropriate trust strategy becomes a critical managerial decision [27]. In mega projects, trust is not only a core element of relational governance but also functions as a critical transmission mechanism for enhancing innovation performance through the strengthening of collaborative relationships and the facilitation of tacit knowledge sharing [28]. Further research indicates that the relationship between knowledge sharing and innovation performance is largely mediated by network trust, whereas hierarchical culture exerts a significant moderating effect. This forms a “knowledge sharing–network trust–innovation performance” transmission pathway, underscoring the pivotal role of trust in achieving innovation outcomes within complex organizational environments [29]. Such trust encourages the exchange of knowledge and ideas among construction units, facilitates innovation practices, and ultimately improves project innovation performance.
Social exchange theory suggests that organizational members who receive organizational support and encouragement tend to reciprocate. Organizational support fulfills employees’ need for value recognition and allows them to feel respected and appreciated. A high level of organizational support not only strengthens members’ recognition of their contributions but also enhances their perception of organizational care. According to the principle of reciprocity, this perceived support encourages employees to give back through increased effort and commitment, thereby fostering innovation and enhancing organizational performance [30]. Furthermore, organizational support fosters a collaborative atmosphere that promotes the sharing of tacit knowledge, significantly improving the innovation output of R&D teams [31]. Research has shown that organizational support constitutes a critical driver of innovation performance. An empirical study based on the improved M-TISM method found that top management support and technological infrastructure exert the most significant influence on innovation [32]. These findings indicate that managerial support in resource allocation and environmental development not only directly enhances innovation capability but also indirectly improves innovation performance by facilitating resource integration and knowledge sharing. In mega projects, organizational support is an essential prerequisite for ensuring the realization of innovation outcomes. In the context of mega projects, organizational support plays a key role by fostering an inclusive innovation climate, establishing resource-sharing mechanisms, and optimizing innovation resource allocation. This, in turn, stimulates team enthusiasm and ultimately boosts project performance.
In a rapidly changing environment, collaboration is essential for overcoming the limitations of individual knowledge and resource constraints in innovation. Mega projects, due to their multi-participant nature, must navigate complex cross-organizational and cross-functional coordination, making effective cooperation a critical management strategy. Collaboration promotes interaction across disciplines and domains, where the heterogeneity of knowledge and the interaction between individuals can spark new ideas and perspectives. This process expands the organizational knowledge base and improves innovation efficiency [33]. Existing studies have demonstrated that, in the context of mega projects, technological innovation cooperation facilitates the transformation of collaborative innovation outcomes into innovation performance through resource sharing, enhanced communication efficiency, and the mediating role of tacit knowledge sharing [34]. From the perspective of the digital innovation ecosystem, Liu Jingtao et al. [35] found that enterprise digital innovation relies not only on the involvement of multiple heterogeneous actors but also on the establishment of a cross-disciplinary, synergistic mechanism. The effectiveness of cooperation depends not on the dominance of a single stakeholder but on the flexible configuration of roles and the realization of truly collaborative innovation among diverse participants.
Based on this, the following hypotheses are proposed:
H2: 
Organizational culture has a significant positive effect on innovation performance in mega projects.
H2a: 
Trust climate has a significant positive effect on innovation performance in mega projects.
H2b: 
Organizational support has a significant positive effect on innovation performance in mega projects.
H2c: 
Cooperation level has a significant positive effect on innovation performance in mega projects.

2.2. Organizational Context and Tacit Knowledge Sharing

2.2.1. Organizational Structure and Tacit Knowledge Sharing

The organizational structure system establishes a coordinated and efficient organizational framework by clearly defining the scope of duties, responsibilities, and rights of its members. As the arrangement of authority and responsibility, communication mechanism, and collaboration mode, organizational formalization and centralization profoundly influence knowledge-sharing behavior. An empirical study by He Yin and Qiang Maoshan, based on a hydroelectric project, shows that the degree of centralization is significantly negatively correlated with knowledge sharing. This is because excessive centralization limits the autonomy of frontline employees and suppresses informal experience sharing among technical experts, thereby exacerbating organizational knowledge barriers. Formalization builds a collaborative framework for tacit knowledge sharing by clarifying the knowledge transfer path and responsibility. For example, a formalized technical delivery process promotes the sharing of experience between the construction and design teams [36]. However, formalization may be rigidly enforced and limit the flexible transfer of unstructured knowledge, especially in projects with frequent technological iterations, and over-reliance on processes may hinder innovative behavior. It has also been demonstrated in relevant studies that organizational structures characterized by a high degree of formalization and centralization exert a negative impact on knowledge-based dynamic capabilities, thereby exerting an adverse effect on innovation within project teams [37]. Empirical studies have shown that an innovative and cooperative organizational climate promotes social interaction, whereas organizational structures characterized by low formalization, decentralization, and high integration are also conducive to such interaction. Consequently, social interaction functions as a mediating mechanism linking organizational climate and organizational structure with knowledge management [38]. On the whole, the influence of centralization and formalization on tacit knowledge sharing presents a “double-edged sword” effect: moderate formalization reduces the uncertainty of sharing through institutional safeguards but it needs to avoid the rigidity of the process, while decentralized structure enhances the vitality of knowledge flow but may lead to an increase in the cost of coordination. Therefore, in construction projects, a highly centralized structure can lead to information distortion and discontinuity due to the long communication chain, thus hindering the sharing of tacit knowledge.
Based on this, the following hypotheses are proposed:
H3: 
Organizational structure has a significant negative effect on tacit-knowledge-sharing behavior among organizations in mega projects.
H3a: 
Organizational formalization has a significant negative effect on tacit-knowledge-sharing behavior among organizations in mega projects.
H3b: 
Organizational centralization has a significant negative effect on tacit-knowledge-sharing behavior among organizations in mega projects.

2.2.2. Organizational Culture and Tacit Knowledge Sharing

Tacit knowledge refers to experiential knowledge that is difficult to articulate, highly individualized, and context-specific. Unlike explicit knowledge, it is unstructured and cannot be easily codified or transferred through written or verbal instructions. Effective transmission of tacit knowledge typically requires social interaction, observation, and hands-on practice. Empirical research based on the resource-based view further reveals that organizational culture exerts a significant positive effect on knowledge sharing, organizational innovation, and competitive advantage. Moreover, knowledge sharing and organizational innovation serve as complementary partial mediators in the relationship between organizational culture and competitive advantage [39]. Studies have shown that team trust, organizational support, and level of cooperation positively influence tacit knowledge sharing, whereas overly hierarchical communication structures severely hinder it [14]. In the context of mega projects, the temporary nature of project teams and high personnel turnover create a substantial risk of tacit knowledge loss throughout the project lifecycle. However, organizational culture, serving as a soft infrastructure that shapes member behavior, is a key enabler of tacit knowledge sharing and creation.
When a high level of trust is formed between organizations, members are more inclined to share professional knowledge, experience, and innovative ideas with an open mind, thus promoting the positive development of knowledge sharing [40]. There is a significant positive correlation between organizational trust and knowledge sharing. Trust is not a unitary construct but a multidimensional one. Trust in colleagues, organizational management, and direct supervisors significantly predicts knowledge sharing. In contrast, commitment-based trust does not exhibit a significant effect. These findings suggest that different dimensions of trust jointly constitute the core mechanism that facilitates tacit knowledge sharing [41]. In project teams, the level of trust influences knowledge sharing among members. This is because trustworthy members, acting as mutual facilitators, can enhance knowledge sharing and improve creative outcomes [42]. Building on network embedding theory, Ma Yonggang et al. further revealed that the trust level among actors in a relational network is positively correlated with their opportunities for knowledge sharing. A high level of trust can significantly enhance employees’ knowledge acquisition and sharing behavior [43]. These findings indicate that a trustful climate is a critical driving force behind tacit knowledge sharing. In mega projects involving multiple collaborating parties, trust not only facilitates the coordination of inter-organizational behaviors but also promotes knowledge flows through institutional design and relational interaction, thereby enhancing both the willingness and the efficiency of inter-organizational tacit knowledge sharing.
O’Driscoll et al. showed that the higher the level of perceived organizational support, the greater the sense of obligation and responsibility that arises within employees. Accordingly, their willingness to share knowledge also increases [44]. This support can be deconstructed into two categories: instrumental support and socio-emotional support. Existing literature further confirms that when employees perceive that the organization recognizes their value and supports them with resources, they are more likely to share tacit knowledge in return for organizational trust. Organizational support can satisfy the socio-emotional needs of employees and foster a sense of being recognized and respected, which in turn strengthens knowledge interaction and sharing behavior within the organization [45]. Further research shows that differentiated perceived organizational support (DPOS) significantly promotes employees’ knowledge sharing. This effect operates through the mediating role of psychological ownership in inter-organizational teams and is positively moderated by task interdependence [46]. In addition, perceived organizational support (POS) directly enhances employees’ willingness to exchange knowledge and fosters innovative work behavior by increasing the frequency of tacit knowledge sharing within organizations [47]. Other studies indicate that POS significantly promotes knowledge sharing only when employees perceive a high level of job security. This finding highlights the critical moderating role of job security in this relationship [48]. Taken together, this study argues that in the context of mega projects, organizational support not only directly enhances members’ willingness to share knowledge but also significantly strengthens tacit knowledge sharing, moderated by contextual factors such as job security and team collaboration. In doing so, it provides essential support for enhancing project innovation performance.
With the construction industry transforming from labor-intensive to knowledge-intensive, intellectual capital has become a key element in measuring project performance and core competitiveness, and it increasingly needs to be generated through more high-quality inter-organizational collaboration. A high level of collaboration fosters knowledge sharing by enhancing trust and communication efficiency among participating organizations. Informal interactions, such as cross-departmental collaboration meetings and community of practice activities, break down organizational and departmental barriers and build networks of trust through frequent interpersonal contacts and emotional exchanges, prompting technologists to proactively share experiential knowledge and skills [33]. Secondly, the structured character of the cooperation level serves as a foundational guarantee for effective tacit knowledge transfer. Research shows that both relational and structural cooperation can promote tacit knowledge transfer. However, relational risks in the cooperation process may inhibit tacit knowledge sharing, especially in sectors with strong technological monopoly, where partners tend to selectively withhold key knowledge out of intellectual property protection concerns [49]. In cooperative relationships, contract completeness and shared goals jointly influence the acquisition of tacit knowledge. The effect of contract completeness on tacit knowledge sharing exhibits an inverted U-shaped pattern. This suggests that a moderate level of contractual governance maximizes the effectiveness of tacit knowledge sharing in cooperative relationships [50]. Compared with the relative stability of enterprises, complex projects involve a greater number of temporary organizations (e.g., designers, constructors, and supervisors). Their cooperation networks are more dynamic, and the short-term goal orientation may undermine the long-term effectiveness of tacit knowledge sharing. As a result, the inhibitory impact of relational risk may be more pronounced in such contexts [11]. Existing research grounded in game theory indicates that, in construction projects, the willingness of owners and contractors to transparently share tacit knowledge directly determines both their mode of cooperation and the resulting project payoffs. When partners refrain from sharing knowledge due to a lack of trust, the cooperative equilibrium often falls short of the optimal level. As a result, synergistic effects cannot be achieved, thereby highlighting the detrimental impact of relational risk on tacit knowledge sharing [11]. It can be seen that collaboration is a critical driver of inter-organizational tacit knowledge sharing, which significantly enhances the effectiveness of tacit knowledge utilization by promoting knowledge flow and integration.
In summary, the following hypotheses are proposed:
H4: 
Organizational culture has a significant positive effect on tacit-knowledge-sharing behavior among organizations in mega projects.
H4a: 
Trust climate has a significant positive effect on tacit-knowledge-sharing behavior among organizations in mega projects.
H4b: 
Organizational support has a significant positive effect on tacit-knowledge-sharing behavior among organizations in mega projects.
H4c: 
Cooperation level has a significant positive effect on tacit-knowledge-sharing behavior among organizations in mega projects.

2.3. The Mediating Role of Implicit Knowledge Sharing

2.3.1. Tacit Knowledge Sharing and Innovation Performance

Mega projects, due to their unique nature, require a great deal of professional technical knowledge for their implementation and management. The inter-organizational sharing and transfer of tacit knowledge is a key driver of innovation. Its core lies in the systematic transmission of individual-held tacit knowledge, such as professional skills, accumulated experience, and innovative thinking. Studies have shown that in a knowledge-driven economy, the absence of tacit knowledge sharing hampers an organization’s ability to create new knowledge and improve both individual and organizational innovation performance [51]. Therefore, enhancing employees’ innovation capabilities is inseparable from effective organizational knowledge sharing and exchange. In today’s rapidly evolving environment, tacit knowledge sharing leads to innovation as it helps organizations to identify and solve problems quickly and effectively [52]. Empirical studies have found that explicit knowledge sharing exerts no significant effect on innovation performance, whereas tacit knowledge sharing significantly enhances organizational performance. This finding highlights the unique role of tacit knowledge sharing in collaborative innovation within construction supply chains and in realizing project innovation performance, suggesting that tacit knowledge sharing constitutes the critical pathway through which collaborative innovation outcomes are transformed into innovation performance [51]. In mega projects, the effective integration of knowledge often requires sharing across diverse individuals and organizational units due to the large number of stakeholders involved. Related research demonstrates that inter-organizational knowledge sharing not only enhances firms’ innovation capability but also significantly improves innovation performance, an effect positively moderated by both network strength and network scale [53]. This implies that, in complex project environments, cross-organizational knowledge sharing serves both as a vital mechanism for resource complementarity and capability synergy and as a key pathway for enhancing innovation performance in mega projects. Based on this, the following hypothesis is proposed:
H5: 
Tacit knowledge sharing has a significant positive effect on innovation performance in mega projects.

2.3.2. The Mediating Role of Tacit Knowledge Sharing

In mega projects, tacit knowledge sharing is a crucial mediating mechanism, connecting the organizational context and innovative performance. Its theoretical basis mainly stems from the resource-based theory and the social exchange theory, jointly forming a theoretical support system for the flow of tacit knowledge. Based on the resource-based theory, knowledge synergy creates competitive advantage by integrating internal and external heterogeneous knowledge resources, while tacit knowledge sharing capability, as a core mediating variable, can transform decentralized technological experience into systematic innovation capability [54]. Social exchange theory further elucidates the motivational mechanism behind tacit knowledge sharing. In the temporary organizations typical of mega projects, members are inclined to reciprocate organizational support through tacit knowledge sharing, driven by cooperation expectations and trust relationship, thereby enhancing project management performance [55]. Sound knowledge governance and tacit knowledge sharing constitute essential prerequisites for enhancing organizational absorptive capacity and improving project performance. Social dynamics further reinforce the interconnections among tacit knowledge sharing, absorptive capacity, and project outcomes. This evidence suggests that tacit knowledge sharing functions as a critical mediating mechanism in the process through which organizational context influences innovation performance. It not only directly facilitates innovation activities but also promotes the realization of project innovation outcomes through the enhancement of absorptive capacity [56]. An organizational culture that emphasizes learning, trust, and cooperative innovation, as well as a decentralized and flexible organizational structure, can effectively stimulate the willingness and behavior of organizational members to share tacit knowledge and promote cross-departmental tacit knowledge flow. Tacit knowledge sharing accelerates knowledge transmission, transfer and integration, and significantly improves the knowledge integration capability of the organization, which in turn promotes technology innovation cooperation innovation performance [34].
Based on this, the following hypotheses are proposed:
H6: 
Tacit knowledge sharing mediates the relationship between organizational context and innovation performance in mega projects.
H6a: 
Tacit knowledge sharing mediates the relationship between organizational culture and innovation performance in mega projects.
H6b: 
Tacit knowledge sharing mediates the relationship between organizational structure and innovation performance in mega projects.
The research model constructed in this paper is shown in Figure 1.

3. Research Methodology

3.1. Data Collection

This study collected data through a questionnaire survey to test the validity of the hypotheses. The questionnaire items were adapted from validated measurement scales established in previous studies. The target respondents were professionals with experience in mega projects, and the research incorporated both questionnaire surveys and field interviews for data collection. Before the official distribution, 70 questionnaires were distributed through the pre-research process, and 62 questionnaires were validly recovered; the semantic ambiguities and ill-structured questions in the questionnaires were corrected. The final questionnaires were distributed through a combination of field visits and online research platforms. A total of 300 questionnaires were distributed, and 267 were returned. After removing responses with significant errors or missing data, 243 valid questionnaires were retained for analysis, resulting in an effective response rate of 91.01%. Regarding the professional affiliation of the respondents, 20% were project owners, 8% were surveyors or designers, 15% were constructors, 26% were general contractors, 4% were supervisors, 7% were engineering consultants, 11% were from research institutes, 5% were government officials, and 4% were from other related units.

3.2. Questionnaire Design and Measurement of Variables

This study constructs a measurement framework for the study variables based on existing theoretical results. In the empirical research design, the measurement tools were selected from validated and mature scales, and all the observed indicators were quantitatively assessed using the internationally recognized Likert five-point scale to ensure measurement reliability and validity. Scales ranging from 1 to 5 indicate complete disagreement, disagreement, fair agreement, comparative agreement, and complete agreement. The trust climate, organizational support, and cooperation level in organizational culture were measured using the scales developed by Du Yaling [57], Eisenberger [58], and Cruz and Carlos Oliveira [59], respectively, with 4 items each; the formalization and centralization degree in organizational structure were both measured using the scale developed by Cheng F. [60] with a total of 8 items; tacit knowledge sharing was measured using the scale developed by Bock [61] with a total of 4 items; innovation performance adopts the scale developed by Zhang Guang lei [62] with 4 items.

4. Results

4.1. Reliability and Validity Test

4.1.1. Reliability Test

To assess common method bias, Harman’s single-factor test was conducted. The results indicated that the variance explained by the first unrotated factor was 31.90%, which is below the critical threshold of 40%, suggesting that common method bias is not a serious concern in this study. Reliability and validity tests were subsequently performed using SPSS 27.0® and AMOS 26.0®. The internal consistency of each construct was evaluated using Cronbach’s alpha. As seen in Table 1, the reliability coefficients of the three first-order variables of organizational context, tacit knowledge sharing, and innovation performance and their secondary dimensions are in the range of 0.7–1, indicating that the questionnaire design has good internal consistency and the quality of the data meets the requirements of reliability.

4.1.2. Validity Test

To test whether the data satisfy the conditions of factor analysis, KMO test and Bartlett’s sphere test were performed using SPSS 27.0® software. After the test, the KMO value reaches 0.897, and the significance of Bartlett’s test is 0, indicating that there is a significant correlation between the variables. The test results indicate that the data fully satisfy the factor analysis prerequisites.
First, Amos 26.0® software was used to conduct the model fitness test, and the model fit indices were as follows: CMIN/DF = 2.197 (between 1 and 3 desirable intervals), RMSEA = 0.070 (<0.08 acceptable threshold), IFI = 0.889, CFI = 0.875, and TLI = 0.888 (all reached the acceptable level of 0.8). The specific data are shown in Table 2. Therefore, the model has good goodness of fit.
As shown in Table 3, in terms of convergent validity, the AVE values of the organizational formalization, organizational centralization, trust climate, organizational support, cooperation level, tacit knowledge sharing, and innovation performance are 0.560, 0.585, 0.673, 0.591, 0.592, 0.552, and 0.527, respectively, all of which are greater than 0.5; the CR values are 0.836, 0.849, 0.891, 0.851, 0.851, 0.829, and 0.814, respectively, formalization of which are greater than 0.7. This indicates good convergent validity of the model.
As shown in Table 4, the square root of AVE is greater than the correlation coefficients between the latent variables, indicating that the model has good discriminant validity.

4.2. Hypothesis Testing Analysis

4.2.1. Direct Effect Test

The validity of the research hypotheses was assessed based on the standardized path coefficients (β) and corresponding significance levels (p), as shown in Table 5. For organizational structure, formalization shows no significant direct effect on innovation performance (β = –0.003, p = 0.956), indicating that Hypothesis H1a is not supported. In contrast, centralization has a significant negative effect (β = –0.274, p < 0.001), supporting Hypothesis H1b. Regarding organizational culture, trust climate (β = 0.236, p < 0.001) and organizational support (β = 0.165, p = 0.009) have significant positive effects on innovation performance, supporting Hypotheses H2a and H2b. However, the effect of cooperation level (β = 0.119, p = 0.075) is not statistically significant, and thus Hypothesis H2c is not supported. Neither formalization (β = –0.017, p = 0.678) nor centralization (β = –0.091, p = 0.129) significantly affects tacit knowledge sharing, indicating that Hypotheses H3a and H3b are not supported. With regard to tacit knowledge sharing, all three organizational culture variables—trust climate (β = 0.282, p < 0.001), organizational support (β = 0.295, p < 0.001), and cooperation level (β = 0.151, p = 0.010)—exert significant positive effects, supporting Hypotheses H4a, H4b, and H4c. Finally, tacit knowledge sharing has a significant positive impact on innovation performance (β = 0.216, p = 0.018), supporting Hypothesis H5.

4.2.2. Test of Mediating Effect

The mediation effect was tested using the PROCESS macro in SPSS 27.0®, with the Bootstrap resampling method applied to evaluate the indirect effects of tacit knowledge sharing. The results of the mediation effect test are shown in Table 6. The statistical results show that the mediation effect values of tacit knowledge sharing presented in the relationship between the dimensions of the organizational context and innovation performance do not contain 0 within the 95% confidence interval, indicating that the mediation effects are statistically significant. Therefore, research hypotheses H6a and H6b are supported.

5. Discussion

This study empirically investigates the influence of organizational context on innovation performance in mega projects. At the structural level, centralization exerts a significant inhibitory effect, whereas formalization shows no direct impact. In highly centralized environments, the excessive concentration of decision-making authority limits frontline teams’ autonomy and capacity for experimentation, thereby constraining creativity and flexibility. Unlike Damanpour [20] and Zhou Guohua [14], who found that formalization hinders innovation in corporate and project-based settings, this study demonstrates that, in multi-stakeholder mega projects, its effect is context-dependent. Under decentralized conditions, formalization—through institutionalized procedures and standardized frameworks—mitigates uncertainty, delineates responsibilities, and fosters cross-organizational knowledge integration. Thus, whereas centralization consistently imposes a negative effect, formalization exerts dual, context-contingent influences. Further analysis indicates that neither centralization nor formalization alone significantly influences tacit knowledge sharing. However, their combination severely restricts informal exchanges, corroborating the “over-rigidity effect” described in institutional complementarity theory [63]. Accordingly, this study advocates a “decentralization–formalization” structure that balances flexibility and control, reduces decision bottlenecks, and provides institutional safeguards for knowledge sharing. Characterized by decentralized decision-making and clear procedural norms, this configuration alleviates the constraints of centralization and fosters cross-organizational tacit knowledge flows, providing organizational assurance for sustainable knowledge sharing.
Secondly, at the cultural level, this study aligns with Boadu [30] and Rajan [33], confirming that a climate of trust and organizational support significantly enhances both innovation performance and tacit knowledge sharing. However, this finding contrasts with Liu Jingtao [36], who argued that inter-organizational cooperation exerts no direct on innovation performance, likely because of the complexity and multi-stakeholder nature of mega projects. Without deep collaborative mechanisms, cooperation often remains limited to task allocation or information exchange, hindering substantive innovation outcomes. Only in a high-trust environment can informal communication and experiential sharing transcend organizational boundaries, enabling effective tacit knowledge sharing and improving innovation performance.
Finally, this study highlights the critical mediating role of tacit knowledge sharing in driving innovation performance. Cross-organizational tacit knowledge sharing directly enhances project management efficiency and innovation potential, partially mediates the effects of formalization, centralization, trust climate, and organizational support, and fully mediates the relationship between cooperation and innovation performance. These findings suggest that cooperation alone is insufficient to realize innovation outcomes; only when tacit knowledge sharing is deeply embedded can cooperative relationships translate into substantive innovation performance. Accordingly, project managers should prioritize building trust mechanisms, fostering a supportive knowledge-sharing environment, refining institutional and incentive systems, and promoting cross-organizational learning to fully leverage tacit knowledge sharing’s mediating role.
In summary, this study elucidates the underlying mechanisms linking organizational context, tacit knowledge sharing, and innovation performance in complex engineering projects. The findings contribute to enhancing the efficiency of knowledge transfer and integration while providing institutional and cultural safeguards for achieving innovation performance. Moreover, they provide systematic support for a paradigm shift in knowledge management and the governance of complex engineering projects.

6. Conclusions and Implications

From a mega project management perspective, this study used questionnaire data and applied Structural Equation Modeling (SEM) to examine the relationship between organizational context and innovation performance. The analysis focused on two core dimensions—organizational structure and organizational culture—with tacit knowledge sharing as a mediating variable. Results indicate that organizational structure, particularly centralization, has a significant negative effect on innovation performance, whereas formalization shows context-dependent effects. Organizational culture, especially a climate of trust and organizational support, positively influences both tacit knowledge sharing and innovation performance. By contrast, cooperation alone does not directly enhance innovation performance, but its effect becomes significant when mediated by tacit knowledge sharing. Among these factors, tacit knowledge sharing is the strongest driver of innovation performance, followed by trust climate and organizational support, whereas centralization functions mainly as an inhibiting factor.
Theoretically, this study elucidates the mediating role of tacit knowledge sharing between organizational context and innovation performance, thereby extending the scope of research on knowledge management and innovation performance. It advances understanding of how organizational structure, culture, and cooperative mechanisms jointly shape innovation outcomes. Moreover, the proposed “organizational context–tacit knowledge sharing–innovation performance” framework offers a novel reference for governing complex engineering projects and advancing knowledge integration research. Practically, this study offers important managerial implications. Project managers should prioritize building trust mechanisms, fostering a supportive organizational climate, and adopting a “decentralization–formalization” structure to reduce bottlenecks and promote cross-organizational knowledge sharing. However, implementing such a structure poses challenges, particularly in large-scale, multi-stakeholder projects. A balanced approach—characterized by “strategic centralization and decentralized execution” supported by digital platforms (e.g., BIM and digital twins), and reinforced by contracts, performance evaluation, and joint governance bodies—can reconcile flexibility with control. In this way, decentralization mitigates bottlenecks, while formalization provides safeguards for cross-organizational collaboration and knowledge sharing. Together, these mechanisms yield valuable insights for enhancing innovation performance in mega projects.

7. Limitations

Despite its contributions to revealing the mechanisms linking organizational context, tacit knowledge sharing, and innovation performance in mega projects, this study has several limitations. First, reliance on cross-sectional survey data captures only static associations, making it challenging to track the dynamic evolution of organizational structures, cultures, and knowledge-sharing mechanisms throughout the project lifecycle. Future research should employ longitudinal designs and collect processual data from mega projects to more accurately capture temporal relationships and evolutionary trajectories, thereby strengthening causal inference and model robustness. Second, because this study is grounded in the Chinese context, it does not consider potential moderating effects of cross-national cultural differences. In international mega projects, cultural dimensions such as power distance, collectivism, and uncertainty avoidance may significantly shape the relationships among organizational culture, tacit knowledge sharing, and innovation performance. Future research should draw on cross-cultural management theories and cultural dimension frameworks to examine these effects, thereby enhancing the model’s generalizability and explanatory power. Finally, this study focuses on organizational context and tacit knowledge sharing as core drivers. Although this clarifies their mechanisms, the model’s explanatory power remains limited. Future research should incorporate additional variables such as project scale and the use of digital tools (e.g., BIM and digital platforms) to build a more comprehensive multi-factor model of innovation performance. This will enhance the completeness and external validity of the framework.

Author Contributions

Conceptualization, H.K. and Y.L.; methodology, H.K. and Y.L.; software, Y.L.; validation, H.K., Y.L. and X.L.; investigation, Y.L.; data curation, Y.L.; writing—original draft preparation, Y.L.; writing—review and editing, H.K.; supervision, H.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to its anonymous survey methodology, which involved no collection or storage of personally identifiable information. The research posed no psychological or social risks to participants.

Informed Consent Statement

This study collected relevant data solely through questionnaire surveys with the aim of acquiring participants’ subjective information. The research employed an online questionnaire method, where respondents completed the survey anonymously, thus involving no personal privacy concerns. All participants were informed of the relevant details and had full awareness of the survey’s content and procedure prior to its commencement. Therefore, no separate informed consent form was required.

Data Availability Statement

Some or all data that support the findings of this study are available from the corresponding author upon reasonable request. All figures and diagrams were created by the authors.

Acknowledgments

The authors would like to sincerely thank all the anonymous participants who completed the questionnaire survey for their valuable time and insights.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
CMIN/DFChi-square/Degrees of Freedom
RMSEARoot Mean Square Error of Approximation
IFIIncremental Fit Index
TLITucker–Lewis Index
CFIComparative Fit Index
CACronbach’s Alpha
FLFactor Loading
CRComposite Reliability
AVEAverage Variance Extracted
S.E.Standard Error
C.R.Critical Ratio
pp-value

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Buildings 15 03237 g001
Figure 1. Theoretical model.
Figure 1. Theoretical model.
Buildings 15 03237 g001
Table 1. Reliability analysis of the scale.
Table 1. Reliability analysis of the scale.
VariablesCAItem Count
Organizational Formalization (OF)0.8344
Organizational Centralization (OCe)0.8474
Organizational Structure (OSt)0.8888
Trust Climate (TC)0.8874
Organizational Support (OSu)0.8444
Cooperation Level (CL)0.8454
Organizational Culture (OCu)0.89912
Organizational Context (OCo)0.77720
Tacit Knowledge Sharing (TKS)0.8524
Innovation Performance (IP)0.8424
Table 2. Model fit test.
Table 2. Model fit test.
IndicatorReference StandardMeasured Results
CMIN/DF1–3 excellent, 3–5 good2.197
RMSEA<0.05 excellent, <0.08 good0.070
IFI>0.9 excellent, >0.8 good0.889
TLI>0.9 excellent, >0.8 good0.875
CFI>0.9 excellent, >0.8 good0.888
Table 3. Results of convergent validity analysis.
Table 3. Results of convergent validity analysis.
Variable ItemFLCRAVE
Organizational FormalizationOF10.7870.8360.56
OF20.762
OF30.766
OF40.674
Organizational CentralizationOCe10.8160.8490.585
OCe20.807
OCe30.746
OCe40.684
Trust ClimateTC10.9460.8910.673
TC20.767
TC30.752
TC40.803
Organizational SupportOSu10.9130.8510.591
OSu20.656
OSu30.766
OSu40.716
Cooperation LevelCL10.9360.8510.592
CL20.738
CL30.645
CL40.73
Tacit Knowledge SharingTKS10.9120.8290.552
TKS20.684
TKS30.66
TKS40.688
Innovation PerformanceIP10.860.8140.527
IP20.637
IP30.755
IP40.626
Table 4. Results of distinctive validity analysis.
Table 4. Results of distinctive validity analysis.
ItemTCOSuCLOFOCeTKSIP
TC0.673
OSu0.470.591
CL0.5370.5230.592
OF−0.221−0.252−0.2510.56
OCe−0.193−0.209−0.1690.6620.585
TKS0.5510.5010.423−0.267−0.2130.552
IP0.4540.4180.425−0.422−0.3440.440.527
Table 5. Hypothesis standard path coefficient and test results.
Table 5. Hypothesis standard path coefficient and test results.
HypothesisPathStandardized Path CoefficientsS.E.C.R.pTesting Results
H1aOF→IP−0.0030.048−0.0550.956Not Supported
H1bOCe→IP−0.2740.073−3.776***Supported
H2aTC→IP0.2360.0623.81***Supported
H2bOSu→IP0.1650.0762.158**Supported
H2cCL→IP0.1190.0671.74810.075Not Supported
H3aOF→TKS−0.0170.041−0.4160.678Not Supported
H3bOCe→TKS−0.0910.06−1.520.129Not Supported
H4aTC→TKS0.2820.0525.387***Supported
H4bOSu→TKS0.2950.0664.448***Supported
H4cCL→TKS0.1510.0582.63**Supported
H5TKS→IP0.2160.0912.371*Supported
Note: * means p < 0.05; ** means p < 0.01; *** means p < 0.001.
Table 6. Results of the mediation effect test.
Table 6. Results of the mediation effect test.
PathEffect ValueStandard ErrorBias-Corrected 95% CI
LowerUpper
OF→YX→CX−0.0950.029−0.155−0.042
OCe→YX→CX−0.0730.027−0.128−0.022
TC→YX→CX0.1270.0340.0610.194
OSu→YX→CX0.1450.0380.0750.221
CL→YX→CX0.1260.0330.0690.199
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Kan, H.; Li, Y.; Li, X. The Influence Mechanism of Organizational Context and Tacit Knowledge Sharing on Innovation Performance in Mega Projects. Buildings 2025, 15, 3237. https://doi.org/10.3390/buildings15173237

AMA Style

Kan H, Li Y, Li X. The Influence Mechanism of Organizational Context and Tacit Knowledge Sharing on Innovation Performance in Mega Projects. Buildings. 2025; 15(17):3237. https://doi.org/10.3390/buildings15173237

Chicago/Turabian Style

Kan, Hongsheng, Yujuan Li, and Xue Li. 2025. "The Influence Mechanism of Organizational Context and Tacit Knowledge Sharing on Innovation Performance in Mega Projects" Buildings 15, no. 17: 3237. https://doi.org/10.3390/buildings15173237

APA Style

Kan, H., Li, Y., & Li, X. (2025). The Influence Mechanism of Organizational Context and Tacit Knowledge Sharing on Innovation Performance in Mega Projects. Buildings, 15(17), 3237. https://doi.org/10.3390/buildings15173237

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