While previous studies highlight the significance of leadership styles in shaping employees’ innovative behavior, the underlying mechanisms remain unclear. Integrating social exchange theory and knowledge creation theory, this study examines the impacts of inclusive leadership and tacit knowledge sharing on employees’ innovative behavior, with tacit knowledge sharing as a mediator and work tenure as a moderator. This study adopted a questionnaire survey method to collect valid sample data from 283 employees in Chinese enterprises, and used hierarchical regression to test the hypotheses. The results show that inclusive leadership has an inverted U-shaped impact on employees’ innovative behavior. Tacit knowledge sharing also exerts an inverted U-shaped effect on employees’ innovative behavior and mediates the relationship between inclusive leadership and employees’ innovative behavior. Additionally, work tenure positively moderates the relationship between inclusive leadership and employees’ innovative behavior, while negatively moderating the relationship between inclusive leadership and tacit knowledge sharing. Overall, these findings enrich the theoretical understanding of the relationship between inclusive leadership and employees’ innovative behavior and provide valuable managerial implications for promoting employees’ innovative behavior.
With the continuous development of artificial intelligence, the business environment has become increasingly complex (Babina et al., 2024). Sustained innovation has become a crucial resource for organizational survival, and employees’ innovative behavior plays a key role in driving this process and supporting enterprise development (Zhang & Yang, 2021; Zhang et al., 2025). Employees’ innovative behavior refers to the process by which employees identify opportunities, generate ideas, seek support from superiors or teams, develop reasonable implementation plans, and integrate existing resources to carry out innovative actions (Malibari & Bajaba, 2022). Accordingly, understanding how to stimulate employees’ innovative behavior to maintain organizational competitive advantage has become a core issue in both management practice and theoretical research.
Leadership styles significantly influence employees’ attitudes and behaviors in the workplace (AlNuaimi et al., 2022; Goswami & Agrawal., 2023; Kang et al., 2015), thereby fostering innovation and creativity within organizational contexts (Karatepe et al., 2020). However, in the digital era, the continuous emergence of technologies such as artificial intelligence and big data has rendered the corporate environment particularly complex and turbulent. This has heightened organizations’ demand for creativity, adaptability, and innovation (Janssen et al., 2025). In such a dynamic and uncertain landscape, effective leadership has become a critical driver of sustained competitive advantage for enterprises (Hughes et al., 2018). In contrast, traditional leadership styles characterized by control, hierarchy, and rule orientation are limited in their effectiveness under these new circumstances. This has led to the adoption of a new leadership style, namely, inclusive leadership (Randel et al., 2018).
Inclusive leadership is relationship-oriented, emphasizing bidirectional interactions between leaders and employees while being characterized by openness, accessibility, and availability (Carmeli et al., 2010; Korkmaz et al., 2022). Although it shares conceptual similarities with other positive leadership styles, it possesses a distinct theoretical core that extends beyond empowering, humble, or participative leadership. Specifically, while empowering leadership focuses on autonomy and participative leadership emphasizes involvement in decision-making (Dennerlein & Kirkman, 2022), they often overlook the inherent tension between individual uniqueness and collective belongingness (Korkmaz et al., 2022; Randel et al., 2018). Similarly, humble leadership promotes learning from followers, yet it lacks the proactive openness and accessibility required to create a safe climate for high-risk innovative trials (Kelemen et al., 2023; Li et al., 2025). Inclusive leadership uniquely addresses this tension by ensuring that employees feel both included within group and valued for their differences (Carmeli et al., 2010). This dual focus is particularly critical for heterogeneous knowledge integration, the cornerstone of employee innovation. By proactively inviting diverse perspectives and remaining accessible, inclusive leaders can lower the barriers to tacit knowledge sharing in ways that mere empowerment or participation cannot (Li et al., 2025; Liu et al., 2025).
Prior literature has predominantly focused on the positive impacts of inclusive leadership (Javed et al., 2021; Wu & Li, 2023; Zafar et al., 2024; Zhong et al., 2022). Grounded in social exchange theory and its inherent reciprocity norms, scholars argue that inclusive leaders create a supportive environment by providing essential socio-emotional support (Carmeli et al., 2010; Choi et al., 2017). By valuing employees’ uniqueness and promoting a sense of belongingness (Randel et al., 2018), they enhance psychological safety, creative self-efficacy, and autonomous motivation (Javed et al., 2021; Li & Tang, 2022; Zafar et al., 2024). Consequently, employees reciprocate this high-quality relational exchange by engaging in innovative behaviors (Ashikali et al., 2021; Singh et al., 2025; Zhang & Zhao, 2024). Within this linear paradigm, inclusive leadership has consistently been viewed as a vital catalyst for organizational inclusion climates and innovative performance (Wu & Li, 2023; Zhong et al., 2022). However, some studies have focused on the possible negative outcomes of inclusive leadership on employees (e.g., lowered task performance and reduced creativity) ( Zheng et al., 2018; Zhu et al., 2020), suggesting its potential drawbacks. Recent scholarly debates have pointed out that inclusive leadership faces tensions when balancing belongingness and uniqueness, where misaligned inclusiveness may lead to persistent conflicts and potential challenges (Zheng et al., 2025). Meanwhile, other studies have argued that inclusive leadership may increase role overload and stress among project managers (Zaman et al., 2024), triggering identity threats and dysfunctional outcomes (Lagowska et al., 2025). This stark contrast between the bright and dark sides suggests that the impact of inclusive leadership on employees’ innovative behavior is likely curvilinear rather than strictly linear. Yet, two critical gaps remain in the current discourse: (1) a systematic theoretical framework explaining this curvilinear (inverted U-shaped) relationship remains underdeveloped, leaving the optimal “sweet spot” of inclusive leadership unidentified. (2) The “black box” of its underlying mechanism and boundary conditions needs to be opened.
Existing research suggests that the influence of inclusive leadership on innovative behaviors may operate through mediating mechanisms, and scholars are encouraged to explore these underlying processes (Hughes et al., 2018; Zhang & Zhao, 2024). However, no research has yet explored this relationship from the perspective of tacit knowledge sharing. Studies have shown that inclusive leadership, by encouraging cross-hierarchical dialogue and experience sharing, may serve as a key catalyst for the dissemination of tacit knowledge (Ashikali et al., 2021; Carmeli et al., 2010; Singh et al., 2021). Individual tacit knowledge is transformed into organizational knowledge assets through socialization and externalization, thereby promoting innovative behavior (Konno & Schillaci, 2021). However, overly inclusive leadership may cause tacit knowledge sharing to exceed the optimal threshold, resulting in information overload or cognitive strain. Consequently, the “too-much-of-a-good-thing” (TMGT) effect may occur, inhibiting employee innovative behaviors. Therefore, this study argues that tacit knowledge sharing serves as a key behavioral pathway through which inclusive leadership exerts a non-linear impact on innovative behavior. Additionally, research indicates that employees’ work tenure influences their work attitudes, cognition, and behaviors (Ng & Feldman, 2011). To further examine this mechanism, this study introduces work tenure as a moderating variable to capture the boundary effect of leadership style on the relationship between knowledge sharing and innovative behavior.
Drawing on a sample of 283 employees in Chinese enterprises, this study develops a moderated mediation model to explain how inclusive leadership influences employees’ innovative behavior, focusing on the mediating path of tacit knowledge sharing and the moderating role of work tenure. This research contributes to the existing literature in two primary ways: First, by identifying the inverted U-shaped impact of inclusive leadership on innovative behavior, it transcends the conventional linear paradigm and provides empirical evidence for the TMGT effect of inclusiveness in complex organizational settings. Second, it uncovers the internal transmission mechanism of this non-linear relationship through the lens of tacit knowledge sharing, while integrating work tenure as a dynamic moderator to reveal how employee seniority functions as a crucial contingency factor in the leadership-innovation nexus.
Theoretical background and hypotheses developmentSocial exchange theory and knowledge creation theoryThe social exchange theory and knowledge creation theory offer a valid theoretical lens for explaining the relationships among the variables in this study. The social exchange theory emphasizes social interactions between parties engaged in knowledge exchange, positing that various relationships established between individuals and all behaviors occurring within society are inherently characterized by an exchange nature (Blau, 1964). Employees’ attitudes and enthusiasm towards information exchange depend on the feedback and openness of others (Cropanzano et al., 2017; Meira & Hancer, 2021). Inclusive leadership, characterized by accessibility, openness, and availability, can shape a harmonious, democratic, and coordinated work environment (Randel et al., 2018). It grants employees a high degree of autonomy and psychological safety, thereby facilitating knowledge sharing and circulation within organizations (Eskerod et al., 2015; Rezaei et al., 2022), particularly tacit knowledge, and laying a knowledge foundation for employees’ innovative behavior. Drawing on the social exchange theory, inclusive leaders establish high-quality social exchange relationships with employees through open communication, recognition, and tolerance of mistakes (Blau, 1964). Within such relationships, employees perceive leadership support and reciprocate with innovative behaviors. For instance, they are more inclined to actively engage in creative activities (Liu et al., 2012). However, excessive inclusiveness may shift the focus of social exchange from team contribution to loyalty to the leader (Humberd & Rouse, 2016; Ma & Tang, 2023). In such cases, employees may avoid challenging ideas to maintain harmonious relationships, thereby limiting the critical thinking required for innovation (Carnevale et al., 2020).
Drawing on the knowledge creation theory, innovation is essentially a process through which individuals’ tacit knowledge is transformed into explicit innovative outcomes through social interaction (López-Cabarcos et al., 2020; Nonaka & Von Krogh, 2009; Park et al., 2022). As a key driver of this transformation, tacit knowledge sharing facilitates the dissemination and development of innovative ideas within organizations through frequent social interaction (Zafar et al., 2024), providing diverse resources and inspiration for employees’ innovation (Akram et al., 2020). However, unlike explicit knowledge, which can be encoded and transmitted at low cost, tacit knowledge is personally embedded, inexpressible, and context-dependent. Its sharing often accompanied by substantial cognitive costs and emotional investment (Holste & Fields, 2010). Thus, when the intensity of tacit knowledge sharing exceeds a specific threshold, frequent unstructured interactions may lead to cognitive overload and resource exhaustion (Hadash et al., 2025). At this point, the cognitive resources consumed to maintain high-intensity interactions will outweigh the marginal information value they generate, thereby crowding out the cognitive resources that employees could otherwise allocate to substantive innovative practices and ultimately hindering innovative behavior (Mehmood et al., 2025).
Inclusive leadership and employees’ innovative behaviorDrawing on the social exchange theory and the TMGT effect, this study posits that the impact of inclusive leadership on employees’ innovative behavior is not a simple positive linear relationship, but rather a non-linear inverted U-shaped pattern characterized by an initial promotional effect followed by an inhibitory effect.
When inclusive leadership increases from a low to a moderate level, high-quality social exchange relationships based on reciprocity effectively stimulate employees’ innovative behavior. First, leaders’ accessibility and availability enable employees to promptly obtain guidance, feedback, and support when needed, thereby facilitating innovation (Carmeli et al., 2010). By respecting individual differences among organizational members and providing them with critical knowledge and financial resources (Zhong et al., 2022), leaders create a supportive innovation climate that enhances employees’ psychological safety and sense of belonging and reduces the social risk costs of innovation (Hirak et al., 2012; Kim et al., 2024). This encourages employees to actively participate in innovation processes and knowledge dissemination (Kang et al., 2016). Second, openness and two-way interaction establish positive emotional bonds (Mitchell & Boyle, 2019). They encourage employees to share new ideas, share knowledge, and suggest improvements (Mitchell & Boyle, 2019), thereby enhancing innovativeness. They also enable leaders to help employees break free from thinking inertia and propose novel solutions by earnestly listening to new ideas, thus facilitating employees’ innovative behavior (Korkmaz et al., 2022). Finally, inclusive leadership endows employees with greater autonomy and independence (Carmeli et al., 2010). By tolerating mistakes and failures in the innovation process, it grants employees sufficient room to exert their strengths in areas of expertise, significantly increasing the likelihood of innovative behavior (Ding et al., 2024).
However, when inclusive leadership exceeds a certain threshold, the focus of reciprocity among team members shifts from the entire team to the leader. Members perceive that sustained focus on team contributions may conflict with the leader’s opinions and decision-making preferences (Carnevale et al., 2020; Ma & Tang, 2023). In this context, team members are more likely to conform rather than challenge the leader, signalling loyalty (Humberd & Rouse, 2016). This inhibits the critical thinking necessary for innovation and limits the generation of diverse ideas. First, excessive openness may lead to information overload and inefficient decision-making (Zheng et al., 2025). Leaders’ undifferentiated acceptance of all viewpoints may result in fragmented opinions, ambiguity, and unclear innovation direction (Liu et al., 2025). It can also induce role ambiguity, undermining both decision-making efficiency and leadership authority (Zheng et al., 2018), and ultimately hindering innovation. Second, excessive accessibility may induce employees’ psychological dependence. While moderate support can stimulate reciprocity, constant availability can reduce employees’ ability to solve problems independently. Over time, this may discourage independent thinking (Ma & Tang, 2023) and suppress the spirit of independent exploration required for innovation. It may also strain leaders’ resources, limiting their ability to support critical innovative activities (Ma & Tang, 2023; Zaman et al., 2024). Finally, excessive psychological safety and tolerance may undermine the “performance-reward” logic in social exchange, weakening employees’ willingness to proactively engage in challenging behaviors. When employees feel fully accepted by the organization, they may see little need to invest additional resources, emotions, and efforts to obtain the already acquired safety and fair status (Zheng et al., 2018), thus reducing their motivation to innovate to demonstrate their abilities and uniqueness (Lam et al., 2015). Furthermore, if leaders blindly tolerate subordinates’ mistakes and failures, employees may fail to learn timely from their mistakes, making it difficult to promote innovative behavior (Ma & Tang, 2023). Without accountability or performance pressure, employees lack career ambition and sense of responsibility, ultimately diminishing their motivation to innovate (Loi et al., 2011; Zheng et al., 2018; Zhu et al., 2020).
Based on the above discussion, we propose the following hypothesis:
H1 Inclusive leadership has an inverted U-shaped impact on employees’ innovative behavior.
Inclusive leadership promotes both uniqueness and belongingness, which enhances employees’ job satisfaction. In an inclusive atmosphere, employees experience team identification (Wu & Li, 2023) while demonstrating their uniqueness through integrating differences and accommodating decision-making differences (Choi et al., 2017; Martin et al., 2013). According to the social exchange theory, relationships between employees and organizations are reciprocal (Blau, 1964). Inclusive leadership provides employees with psychological safety, increasing their acceptance of both the organization’s soft culture and hard systems (Eskerod et al., 2015; Li & Tang, 2022). When employees feel recognized and valued, their sense of insider status strengthens (Lam, 2007; Zhao et al., 2019). Similarly, when leaders demonstrate openness and inclusiveness, employees will be more optimistic about their work content, and their resilience and self-efficacy will gradually improve (Javed et al., 2021). Over time, these factors build psychological capital, enhancing job satisfaction and motivating employees to engage in extra-role behaviors (Hsu & Chen, 2017).
Tacit knowledge sharing is a type of extra-role behavior (Bavik et al., 2018). It involves exchanging personal experiences and knowledge based on trust, allowing employees to break through social dilemmas, internalise knowledge, and generate new ideas (Khan et al., 2023). Social dilemmas mean that when employees share their knowledge, it becomes accessible to others, potentially reducing their competitive edge. Consequently, employees may be hesitant to share knowledge (Zhao et al., 2019). This indicates that tacit knowledge sharing requires frequent knowledge exchange and sufficient trust among organizational members (Capestro et al., 2024). Drawing on the social exchange theory, inclusive leadership significantly reduces these social risks by establishing reciprocal norms and a climate of trust (Iqbal et al., 2023). Specifically, by establishing an inclusive organizational climate, inclusive leadership encourages employees to exchange their unique insights, thereby enhancing their willingness to contribute tacit knowledge (Ashikali et al., 2021). This interactive phenomenon can effectively increase employees’ dependence on the organization, strengthen their perception of insider identity, strengthen their identification with the organization while maintaining their uniqueness (Lam et al., 2007). Trust within the organization enhances cooperation among members and increases the likelihood of sharing tacit knowledge (Al Saifi et al., 2015). In summary, from the perspective of the social exchange theory, inclusive leadership provides employees with valuable inducements. Specifically, it facilitates employees’ tacit knowledge sharing by establishing positive relationships and serving as role models to encourage employees to contribute their knowledge.
H2 Inclusive leadership has a positive impact on tacit knowledge sharing.
Innovation refers to the introduction of new products, services, or processes into the production links or business processes of an enterprise or organization to improve performance (Sarooghi et al., 2015). Employees’ innovative behavior is not only influenced by individual factors but also by their continuous knowledge dissemination, accumulation, and application within the organization (Bouncken et al., 2021; Kucharska & Erickson, 2023). In other words, knowledge forms the foundation for innovative behavior, while knowledge sharing (particularly tacit knowledge sharing) is a critical enabler of innovative behavior (Bruns, 2013; Huarng et al., 2018). The inherent difficulty in encoding and describing tacit knowledge poses challenges to its dissemination (Holste & Fields, 2010). However, its inimitability and context-embeddedness give it a unique strategic value, making it a key source of organizational innovation and sustainable competitive advantage (Castellani et al., 2021). As an effective means of knowledge dissemination, tacit knowledge sharing can accelerate the flow of knowledge within an organization, stimulate employees to learn through interactions with others, and inspire deeper personal thinking (Sheehan et al., 2020). Employees can continuously exchange ideas and provide effective feedback, making it a crucial pathway for employees to reasonably apply knowledge and generate innovative behaviors.
However, once tacit knowledge sharing within an organization exceeds a certain threshold, its impact on employees’ innovative behavior shifts. Employees’ innovative behavior is a complex multi-stage process encompassing idea generation, promotion, and implementation. It requires sustained focus and deep thinking capabilities (Malibari & Bajaba, 2022;Zhang et al., 2025). If employees’ attention is fragmented by disjointed tacit knowledge-sharing activities, they will struggle to engage in high-quality innovation (Kucharska & Erickson, 2023). Drawing on the knowledge creation theory, information overload and cognitive fatigue can reduce employees’ ability to acquire, transform, and internalize new knowledge from external sources (Nonaka & Von Krogh, 2009). This further impairs their capacity to convert tacit knowledge into codified explicit knowledge (Park et al., 2022) and limits their ability to generate ideas or recombine knowledge effectively, thereby inhibiting innovative behavior (Zhou et al., 2025).
Tacit knowledge sharing is not merely a simple information transmission process, but rather a high-intensity cognitive restructuring process (Yıldız et al., 2025). When the volume of tacit knowledge shared within an organization exceeds the optimal processing capacity of individual employees, an imbalance arises between input and absorption (Cristache et al., 2025). In this context, the effective knowledge accessible to employees is overshadowed by vague, redundant, or low-value information, leading to information overload and dilution of cognitive resources (Intezari et al., 2017). This reduces employees’ sensitivity to critical information and compels them to spend more time and effort on information screening, refinement, and integration, reducing the cognitive resources available for innovation (Akram et al., 2020; Huarng et al., 2018). As this cognitive burden accumulates, employees’ knowledge absorption capacity may experience overload, limiting their cognitive restructuring and innovative thinking. This makes it difficult to form the systematic knowledge framework required for innovation (Rezaei et al., 2022). When tacit knowledge sharing becomes excessive, it transforms from a resource into a distraction (Dzenopoljac et al., 2025). Large volumes of unstructured and context-dependent information can overwhelm employees’ working memory, imposing a substantial external cognitive load (Zhang et al., 2022).
Excessive tacit knowledge sharing can also trigger innovation fatigue (Dzenopoljac et al., 2025; Wang & Wang, 2012). Continuous communication, frequent information collisions, and constantly updated knowledge requirements increase employees’ external cognitive load. This leads to psychological exhaustion, as they continuously adjust their cognitive patterns and absorb tacit knowledge (Huarng et al., 2018). When the psychological pressure arising from such high-intensity cognitive restructuring and information processing exceeds employees’ recovery and regulatory capacities, may induce innovation burnout (Bani-Melhem et al., 2018). Innovation burnout not only undermines employees’ willingness to engage in exploring unconventional problems but also reduces their emotional engagement and motivation to participate in complex, ambiguous, and high-risk innovative activities (Bani-Melhem et al., 2018; Singh et al., 2021).
Based on the above analysis, the following hypothesis is proposed:
H3 Tacit knowledge sharing has an inverted U-shaped impact on employees’ innovative behavior.
Knowledge is an important strategic resource and core asset for enterprises (Xu & Cavusgil, 2019). Knowledge sharing, in turn, is a key factor influencing enterprises’ creativity and competitiveness (Yıldız et al., 2025). Among its forms, tacit knowledge sharing is particularly important in linking inclusive leadership to employees’ innovative behavior. According to the social exchange theory, tacit knowledge sharing does not exist in isolation. Instead, it is gradually shaped and cultivated as employees continuously engage deeply with their organizational environment and assigned tasks (Caputo et al., 2021). Over time, employees gradually acquire tacit knowledge in the form of personal work skills, problem-solving approaches, and industry insights (Enwereuzor, 2021). When shared, this knowledge can spark fresh inspiration and innovative ideas, stimulating innovative behavior.
Moderate inclusive leadership helps create a high-trust team climate (Zafar et al., 2024), which encourages employees to share their hard-to-access personal experiences and engage in tacit knowledge sharing (Terhorst et al., 2018; Yang & Farn, 2009). Drawing on the social exchange theory, such behavior triggers reciprocal norms (Blau, 1964), motivating other members to contribute their own wisdom and fostering an ecosystem that supports innovation (Korkmaz et al., 2022). In such an environment, employees feel more confident to put forward bold ideas, knowing they are backed by the team’s knowledge network (Rogozińska‐Pawełczyk & Sudolska, 2024). Specifically, inclusive leadership is committed to creating an open communication environment. By encouraging diverse viewpoints and active listening, it accelerates knowledge flow within the organization, thereby promoting employees’ innovative behaviors (Zhang et al., 2022). This open environment enhances knowledge accessibility, enabling employees to obtain diverse information and resources more conveniently (Piñeiro-Chousa et al., 2020). As a result, employees are more willing to share their insights, facilitating tacit knowledge sharing among organizational members (Kucharska & Erickson, 2023). Through continuous interaction and knowledge exchange, the organization can form a specialized knowledge and skill system characterized by professionalism and complexity, further improving employees’ innovative behavior (Yıldız et al., 2025). Based on the above analysis, the following hypothesis is proposed:
H4 Tacit knowledge sharing mediates the relationship between inclusive leadership and employees’ innovative behavior.
Work tenure refers to the length of time an employee has been with an organization, serving as a critical variable influencing employees’ work attitudes, cognitions, and behaviors (Ng & Feldman, 2011; Singh, 2025). It is not merely a simple linear accumulation of time but rather a diachronic manifestation of the organizational socialisation process. This process enables employees to gradually adapt to the organization, establish trust with supervisors and colleagues, and fulfil their roles (Ng & Feldman, 2011). Drawing on the social exchange theory, employees with long work tenure tend to perceive the innovative space granted by inclusive leadership as recognition. Over time, they accumulate social capital and professional knowledge, which enhances their innovative behavior (Konno & Schillaci, 2021; Kim & Shim, 2018). Accordingly, this study argues that employee’s work tenure may mitigate the inverted U-shaped effect of inclusive leadership on employees’ innovative behavior. Specifically, before inclusive leadership reaches the threshold level, longer work tenure will strengthen its positive impact. However, as inclusive leadership exceeds the threshold level, longer work tenure will alleviate its negative impact on innovation.
From the perspective of the self-determination theory, intrinsic motivation serves as a necessary prerequisite for innovative behavior. Employees’ intrinsic motivation originates from their sense of competence (Gagné et al., 2022; Yu et al., 2024). Employees with long work tenure have not only accumulated extensive job-specific knowledge but also developed affective commitment to the organization (Atatsi et al., 2021), resulting in a significantly higher sense of competence compared to newcomers. When inclusive leadership is at a moderate level, they perceive “inclusiveness” as recognition of their professional capabilities, thereby strengthening their intrinsic motivation and innovative behavior (Choi et al., 2017; Javed et al., 2019). Even if inclusive leadership exceeds the threshold and leads to potential risks, employees with long work tenure can leverage their accumulated experiential knowledge to independently set clear innovative paths (Atatsi et al., 2021), reduce the perceived intensity of uncertainty, and thus mitigate the inhibitory effect on innovation potentially induced by excessive inclusiveness (Ma & Tang, 2023). In contrast, employees with short work tenure are in the stage of role adaptation and competence construction, lacking a systematic understanding of organizational routines (Ng & Feldman, 2011; Singh, 2025). Once inclusive leadership surpasses the critical value, they may become confused and experience innovation stagnation due to role ambiguity and resource disorientation (Zaman et al., 2024).
Additionally, employees with long work tenure often identify strongly with the organization, and perceive the moderate autonomy granted by inclusive leadership as an extension of their responsibilities (Farmer et al., 2003; Singh et al., 2025). Under the guidance of moderate inclusive leadership, employees will proactively expand their responsibility boundaries and increase cross-departmental collaboration behaviors, which enhances their innovative behavior (Bammens, 2016). However, when inclusive leadership exceeds a certain limit and lacks external constraints, employees with long work tenure perceive a lack of control within the organization. They coordinate the team’s innovation direction and control innovation resource utilization to maintain the organizational stability and status (Popa et al., 2017), thereby reducing the negative impact of excessively inclusive leadership on employees’ innovative behavior. Based on this, the following hypothesis has been proposed:
H5 Work tenure positively moderates the inverted U-shaped relationship between inclusive leadership and employees’ innovative behavior.
Tacit knowledge sharing is a high-risk and high-cost form of social exchange behavior (Hau et al., 2013; Kucharska & Erickson, 2023). This study therefore argues that the impact of inclusive leadership on such behavior may vary with employees’ work tenure. For employees with short work tenure, the psychological safety and relational resources provided by inclusive leadership are both scarce and urgently needed, thus driving their tacit knowledge sharing behavior. In contrast, employees with long work tenure derive a sense of safety from their status and experience. This may reduce their dependence on leadership behaviors and sensitivity to reciprocity, thereby weakening the effect of inclusive leadership on tacit knowledge sharing.
Drawing on the social exchange theory, new and senior employees are in different phases of social exchange (Blau, 1964). New employees occupy peripheral positions within the organization and seek to establish high-quality relationships to obtain resources and organizational acceptance. The reciprocal signals transmitted by inclusive leadership motivate them to proactively contribute their tacit knowledge (Castellani et al., 2021). In contrast, the relationship between senior employees and the organization has shifted from short-term reciprocity to long-term trust-based exchange (Humberd & Rouse, 2016; Ma & Tang, 2023). Even when leaders exhibit inclusiveness, senior employees may still choose to retain valuable knowledge and minimize sharing experiences with other members to maximize their own interests (Atatsi et al., 2021). As their tenure increases, their awareness of protecting their knowledge-based power may also strengthen, further undermining the effect of inclusive leadership on knowledge sharing (Singh, 2019). Additionally, research has shown that after long-tenured employees accumulate sufficient organizational trust and social capital, the motivational impact of psychological safety and resource support brought by inclusive leadership on their knowledge-sharing behavior may be weakened (Armstrong-Stassen & Schlosser, 2011).
From the perspective of social learning, individuals are more likely to imitate behaviors when entering a new environment (Malibari et al., 2025). New employees possess high environmental sensitivity and tend to model leaders’ behaviors. When inclusive leaders demonstrate open and knowledge sharing behavior (Randel et al., 2018), new employees will proactively imitate such behavior and integrate into the team through tacit knowledge sharing to gain identity recognition (Zhao et al., 2019). In contrast, senior employees have already formed fixed behavioral patterns, maintaining existing relationships and the status quo. They are less willing to adopt leaders’ behaviors as models or adjust their existing behaviors through imitation (Armstrong-Stassen &, Schlosser, 2011). Thus, when inclusive leadership promotes tacit knowledge sharing among employees, long-tenured employees are more likely to adopt a neutral or wait-and-see strategy, showing lower motivation to learn or adapt (Rhee & Choi, 2017).
From the perspective of organizational identification, employees with long work tenure are more willing to act as mentors and tacit knowledge transmitters in inclusive environments. However, their knowledge sharing behavior is driven by role expectations and a sense of responsibility (Obrenovic et al., 2022) rather than proactive behavior stimulated by inclusive leadership. Additionally, a stronger organizational sense of responsibility may lead them to adopt self-protective measures regarding knowledge governance, aiming to prevent the loss of organizational experience and knowledge caused by excessive tacit knowledge sharing (Pereira & Mohiya, 2021).
Based on the above analysis, this study proposes the following hypothesis:
H6 Work tenure negatively moderates the relationship between inclusive leadership and tacit knowledge sharing.
Based on the above analysis, this study has constructed the theoretical model as shown in Fig. 1.
MethodSample and data collection procedure
This study adopted a random sampling method to collect sample data, following a three-tier logic of “regional representativeness–enterprise randomness–individual pertinence” to ensure sample representativeness and data reliability. Based on the “2020 China Regional Innovation and Entrepreneurship Index Report” released by the National School of Development, Peking University, 50 Chinese enterprises were randomly selected from each category of regions: high-activity regions (Beijing, Shanghai), medium-activity regions (Sichuan, Henan), and low-activity regions (Jilin, Heilongjiang) for innovation and entrepreneurship. The survey covered multiple industries, including manufacturing, services, and high-tech sectors. This stratified sampling strategy not only avoids potential sample bias associated with single-region sampling but also achieves comprehensive coverage of enterprises across regions with different levels of innovation and entrepreneurship development in China, providing a solid sample basis for the cross-regional generalizability of the research findings.
In the survey implementation phase, the research team connected with enterprise representatives through telephone communication and on-site visits. The research purpose, survey content, and questionnaire completion guidelines were clearly explained to the enterprise managers. Participants were assured that all responses would be anonymous and used solely for academic research, with no disclosure of organizational or individual identities. Subsequently, the questionnaires were distributed internally with the assistance of human resources departments or designated contacts.
To enhance data quality and the adaptability of research variables, this study conducted targeted screening of survey participants, clearly defining the inclusion criterion as “core members within enterprises who frequently engage in knowledge and information exchange activities”. Specifically, this includes middle and frontline managers, cross-departmental project team leaders, and key personnel from core departments such as R&D and marketing operations. The screening was based on two primary considerations. First, the core variables of this study (inclusive leadership, tacit knowledge sharing, and employees’ innovative behavior) are closely linked to individuals’ work interaction frequency and the intensity of knowledge acquisition and output. Thus, the work contexts of this group can more accurately reflect the characteristics of these variables. Second, core members possess a more comprehensive and in-depth perception of organizational management models, leadership behaviors, and innovation climates, which reduces potential evaluation bias from limited work exposure.
A total of 500 questionnaires were distributed across 120 enterprises. After questionnaire collection, data cleaning was conducted in accordance with standard procedures. First, questionnaires with excessively short completion time (less than one-third of the average completion time) and patterned responses (e.g. identical answers throughout) were excluded. Second, incomplete questionnaires with missing items for key variables or incomplete demographic information were removed. After screening, 283 valid samples were retained, yielding an effective recovery rate of 56.6%. Detailed information on sample characteristics is presented in Table 1, covering groups with different genders, ages, work tenure, enterprise ownership types, and firm sizes, indicating good overall representativeness.
Sample characteristics.
To test for potential non-response bias, the returned questionnaires were divided into an early response group (first 10%) and a late response group (last 10%). Independent samples t-tests were then conducted on key demographic and organizational characteristic variables of the two groups. The results showed no significant differences between the two groups in three dimensions: age (t = 0.139, p = 0.890), work experience (t = −0.258, p = 0.798), and firm size (t = −1.055, p = 0.296), with all p-values exceeding 0.05. These findings indicated that no significant non-response bias was detected in this study, and that the sample demonstrated strong representativeness across key characteristics.
MeasuresTo test the hypotheses proposed in this study, all key variables adopted mature scales published in reputable journals. These scales are not only aligned with the theoretical framework of this study but have also been validated in multiple cultural contexts, including China. All items were measured using a the 5-point Likert scale, in which “1” indicates “strongly disagree” and “5” means “strongly agree”.
Employees’innovative behavior was measured with the 9-item scale developed by Janssen (2000). This scale encompasses three dimensions, namely, generation, promotion, and implementation of innovative ideas, and has been widely used in research on individual innovative behavior. This scale has also been effectively applied by Peng et al. (2019) in their research on Chinese team creativity, further supporting its construct validity in the Chinese context.
Inclusive leadership was measured using the 8-item scale developed by Carmeli et al. (2010) and Choi et al. (2017). Focusing on the relationship between leadership styles and employee’s behaviors, this scale is highly aligned with the theoretical logic of this study regarding the role of inclusive leadership in stimulating innovative behavior. This scale has recently been successfully applied to the Chinese management context in a study by Mangi et al. (2025), validating its cross-cultural validity.
Tacit knowledge sharing was measured with the 7-item scale developed by Wang and Wang (2012). It specifically captures the informal transfer of experience-based and hard-to-code knowledge among organizational members, aligning with this study’s focus on the “tacit knowledge flow mechanism.” This article has been cited 839 times and has also been applied to the Chinese management context by Wang et al. (2024), validating its applicability to Chinese samples.
In the translation and localization process, we strictly followed the back-translation procedure. A translation team consisting of one professor and two doctoral students first independently completed the English-to-Chinese translation, and then conducted cross-checking to form the initial draft. Subsequently, a bilingual scholar who did not participate in the initial translation was invited to back-translate the Chinese draft into English, which was then compared with the original English version item by item. Furthermore, prior to the formal survey, we selected five corporate executives and 30 frontline employees to conduct in-depth interviews during the pre-testing phase, aiming to identify potential comprehension barriers or culturally mismatched expressions. Importantly, all adjustments were limited to the linguistic expression level, without altering the factor structure, number of items, or theoretical connotation of the original scales. The scales are detailed in Table 3.
Work tenure was categorized into five levels, with specific categories as follows: 1= “<1 year,” 2= “1–10 years,” 3= “11–20 years,” 4= “21–30 years,” and 5= “>30 years”
Drawing on existing research (Newman et al., 2018; Odugbesan et al., 2023), this study selected employee gender, age, position, education, firm type, and firm size as control variables. To control for potential influencing factors at the individual and organizational levels (Eldor, 2017; Jada et al., 2019), this study further incorporated two important control variables: (1) organizational innovation climate, measured with the 4-item scale developed by Oke et al. (2013); and (2) job satisfaction, assessed using the 3-item scale developed by Pugh et al. (2011).
ResultsDescriptive statistics and correlation analysisSPSS 26.0 was used to calculate the means, standard deviations, and Pearson correlation coefficients of the variables in this study. The results of descriptive statistics and correlation analysis are presented in Table 2. These results indicate significant correlations among the key variables, which provides a preliminary basis for further exploring the relationships between them.
Descriptive statistics and correlation analysis.
Notes: The square roots of the average variance extracted are displayed along the diagonal in parenthesis. * p < 0.05, ** p < 0.01.
To effectively mitigate the impact of CMV on this study, both procedural controls and statistical tests were adopted. In terms of procedural controls, respondents were informed that the questionnaire data would be used solely for academic research with guaranteed anonymity. Specialized terms were explained to ensure understanding, and the order of questions was randomly adjusted to avoid systematic response biases. For statistical tests, Harman’s one-factor test was employed to detect potential CMV. The results showed that the variance explained by the first factor was less than 40%. Additionally, employing the full collinearity assessment method for PLS-SEM proposed by Kock (2015), the Variance Inflation Factor (VIF) values of all variables were below 3.3. Therefore, CMV is not a serious concern in this study.
Reliability and validityBefore testing the hypotheses, this study rigorously assessed the reliability and validity of the measures, with results presented in Table 3. The Cronbach’s α coefficients of all variables were above 0.8, indicating good reliability. Individual item reliability was verified through factor loadings. While most loadings exceeded the threshold of 0.70, the loading for item EIB3 was 0.677, which is slightly below 0.70 and marginally within the acceptable range. Removing this item would not significantly improve the overall composite reliability (CR) or average variance extracted (AVE) values. Therefore, we prioritized maintaining the completeness of the scale content and retained this item. Furthermore, the CR values exceeded 0.8, and the AVE values were higher than 0.5, demonstrating favourable convergent validity. As shown in Table 2, the square roots of the AVE for each variable were larger than the correlation coefficients between variables, which indicated good discriminant validity.
Reliability and validity analysis.
The results of hypothesis testing are presented in Table 4. The maximum VIF across all regression models was no more than 2.56, well below the commonly accepted threshold of 10, indicating no serious multicollinearity issues. Given that the sample comprised 283 employees nested within 120 enterprises, all regression models utilized firm-level cluster-robust standard errors to account for potential within-firm correlation in error terms arising from shared organizational contexts, corporate culture, and other factors.
Hypothesis testing results.
Notes: Standard errors in parentheses. * p < 0.05, ** p < 0.01.
In Model 2, inclusive leadership squared had a significant negative effect on employees’ innovative behavior (β = −0.148, p < 0.01), supporting H1 (Fig. 2(a)).
In Model 7, inclusive leadership exerted a significant positive effect on tacit knowledge sharing (β = 0.463, p < 0.01), supporting H2.
In Model 3, tacit knowledge sharing squared had a significant negative effect on employees’ innovative behavior (β = −0.303, p < 0.01), supporting H3 (Fig. 2(b)).
Combining the results of Models 2, 3, 4, and 7, we can conclude that tacit knowledge sharing plays a mediating role in the relationship between inclusive leadership and employees’ innovative behavior, supporting H4.
In Model 5, the interaction term between inclusive leadership squared and work tenure had a significant positive effect on employees’ innovative behavior (β = 0.099, p < 0.01). This indicates that as work tenure increases, the inverted U-shaped relationship between inclusive leadership and employees’ innovative behavior becomes flatter. In other words, the inverted U-shaped effect of inclusive leadership on employees’ innovative behavior is weakened, supporting H5 (Fig. 3(a)).
In Model 8, the interaction term between inclusive leadership and work tenure had a significant negative effect on tacit knowledge sharing (β = −0.145, p < 0.01). This suggests that with the increase in work tenure, the positive relationship between inclusive leadership and tacit knowledge sharing becomes flatter, meaning the positive effect of inclusive leadership on tacit knowledge sharing is weakened, supporting H6 (Fig. 3(b)).
Robustness testsFirst, to test the robustness of the inverted U-shaped relationship and rule out the possibility of a “ceiling effect”, this study employed restricted cubic spline analysis. Knots for inclusive leadership were set at its 25th, 50th, and 75th percentiles (3.5, 4, 4.25) to accurately examine the nonlinear pattern of the main part of the scale. As shown in Table 5, in Model 9, the coefficient of the first spline term was significantly positive (β = 0.357, p < 0.01), while the coefficient of the second spline term was significantly negative (β = −0.302, p < 0.01). The joint test of the spline terms was significant (F (2, 100) = 11.24, p < 0.01), supporting the inverted U-shaped relationship between inclusive leadership and employee innovative behavior. Importantly, the inflection point of the curve appeared around 4 (see Fig. 4(a)), which is far from the theoretical ceiling of the scale (5). This rules out the possibility of spurious effects caused by measurement ceiling. Results of the test for the nonlinear relationship between tacit knowledge sharing and employee innovative behavior are presented in Table 5, which supports the inverted U-shaped relationship (see Fig. 4(b)).
Spline regression results.
Notes: Firm-level cluster-robust standard errors are in parentheses. IL stands for Inclusive Leadership, and TKS stands for Tacit Knowledge Sharing. * p < 0.05, ** p < 0.01.
Additionally, we adopted the three-step testing procedure recommended by Lind and Mehlum (2010) to further test the robustness of the inverted U-shaped relationships in this study, with the results presented in Table 6. Taking the inverted U-shaped relationship between inclusive leadership (IL) and employees’ innovative behavior as an example: (1) The coefficient of the squared term (IL²) was negative and significant (β₂ = −0.147, p < 0.01); (2) The slope at point XL (the lower bound of IL values) was positive and significant (Slope = 0.857, p < 0.01), while the slope at point XH (the upper bound of IL values) was negative and significant (Slope = −0.289, p < 0.01); (3) The turning point and 95% confidence interval based on the standard error of the turning point calculated via Fieller’ s method are within the range of variable values (Turning Point = 4.022, 95% CI [3.691, 4.604]). The test results for the relationship between tacit knowledge sharing and employees’ innovative behavior are also presented in Table 6, which supports the hypothesis that an inverted U-shaped relationship exists.
Tests of the inverted U-shaped effects on adaptive agility1.
| Y = Employees’ innovative behavior | X = Inclusive leadership(Model 2 in Table 4) | X = Tacit knowledge sharing(Model 3 in Table 4) |
|---|---|---|
| β1 (linear term) | 1.190** | 2.490** |
| β2 (quadratic term) | −0.147** | −0.303** |
| Slope at XL (β1 + 2β2XL) | 0.857** (3.649) | 1.365** (5.733) |
| Slope at XH (β1 + 2β2XH) | −0.289** (−2.478) | −0.538**(−2.818) |
| Appropriate U test | 2.48** | 2.82** |
| Extremum point (-β1 / 2β2) | 4.022 | 4.112 |
| 95% confidence interval, Fieller method | [3.691,4.604] | [3.895,4.557] |
Notes: t-values in parentheses. * p < 0.05,** p < 0.01.
Second, this study re-tested the theoretical model based on the PLS-SEM method. The results, presented in Table 7, are consistent with the previous test results.
Hypothesis testing results based on PLS-SEM.
R2TKS = 0.285; R2EIB = 0.230; Q2TKS = 0.205; Q2EIB = 0.124.
Notes:* p < 0.05, ** p < 0.01.
Finally, to ensure the robustness of the mediating effect, we followed the recommendations of Hayes and Preacher (2010) to test the nonlinear mediating effect of tacit knowledge sharing in the inverted U-shaped relationship between inclusive leadership and employees’ innovative behavior. Table 8 presents the instantaneous mediating effect (θ) of tacit knowledge sharing at specific values of tacit knowledge sharing. The results show that when tacit knowledge sharing is at relatively low and moderate levels, the instantaneous mediating effect is significantly positive (θ = 0.184, 95% CI = [0.104, 0.286], excluding 0; θ = 0.111, 95% CI = [0.051, 0.179], excluding 0). When tacit knowledge sharing is at a relatively high level, the instantaneous mediating effect is not significant (θ = 0.037, 95% CI = [−0.049, 0.118], including 0). Therefore, moderate tacit knowledge sharing enables inclusive leadership to positively influence employees’ innovative behavior, while excessive tacit knowledge sharing prevents inclusive leadership from influencing employees’ innovative behavior.
DiscussionAs organizations increasingly rely on innovation performance, employees’ innovative behavior has become critical to sustaining firms’ competitiveness. Despite the increasing body of research on innovative behavior, there remains a lack of consistent theoretical explanations for how inclusive leadership influences employees’ innovative behavior in the complex and dynamic digital context within Chinese enterprises, which are deeply influenced by Confucian culture. The rapid evolution of digital technologies has not only transformed firms’ production methods but also increased task uncertainty and knowledge complexity for employees. Against this backdrop, inclusive leadership, characterized by openness, accessibility, and effective interaction, is regarded as an important leadership style capable of effectively addressing employees’ diverse needs and innovative ideas (Carmeli et al., 2010; Randel et al., 2018). Extant research generally argues that inclusive leadership can stimulate employees’ innovation awareness and enhance organizations’ sustainable competitive advantage in dynamic environments (Bani-Melhem et al., 2018; Zhang et al., 2022). Nevertheless, the following important theoretical questions remain unresolved: Is inclusive leadership always beneficial? Under what conditions might it fail? What are the cultural and organizational boundary conditions? Therefore, deepening the relational mechanisms between inclusive leadership and employees’ innovative behavior not only helps improve theoretical explanatory power but also facilitates an understanding of the innovation operation logic of Chinese enterprises in the digital context.
Based on survey data from 283 employees of Chinese enterprises, this study constructs and validates a mechanistic model of the impact of inclusive leadership on employees’ innovative behavior. The results indicate that the relationship between inclusive leadership and innovative behavior is not a unidirectional linear relationship but rather exhibits an inverted U-shaped effect. Specifically, moderate inclusiveness can promote employees’ innovation, while excessive inclusiveness may lead to diminishing marginal effects of its role and even inhibit innovation. Robustness tests show that the theoretical framework of this study can explain how leaders through their interactional characteristics, stimulate employees’ innovative behavior in a dynamic business environment. The findings support the view of most scholars that inclusive leadership plays a positive role in motivating innovation (Bammens, 2016; Zhang et al., 2025), while breaking through the universally assumed linear hypothesis in previous studies, validating the theoretical inference of Ma and Tang (2023) that inclusive leadership has a curvilinear effect. This discovery fundamentally challenges the leadership assumption that “more inclusiveness is always better” and emphasizes the importance of leadership behavior.
Furthermore, this study deepens the underlying mechanism through which inclusive leadership influences employees’ innovative behavior through tacit knowledge sharing. By respecting employees’ differences and enhancing affect-based and cognition-based trust (Holste & Fields, 2010), inclusive leadership significantly increases employees’ willingness to share experiential, individual, and hard-to-codify tacit knowledge (Enwereuzor, 2021), thereby facilitating the transformation of knowledge into innovative behavior. The findings indicate that tacit knowledge sharing plays a critical mediating role, explaining how knowledge flow can fully unlock innovation potential in the context of moderate inclusiveness. Additionally, employee work tenure moderates the effect of inclusive leadership, reflecting differentiated response mechanisms of employees at different career stages to leadership behaviors. Particularly in the context of China’s high-power-distance culture, senior employees are more likely to experience role ambiguity and reduced motivation in the face of excessive inclusiveness, while a moderate level of inclusiveness is more effective in stimulating their experiential advantages and encouraging knowledge contributions.
Theoretical implicationsThis study makes the following three theoretical contributions.
First, this study validates the inverted U-shaped effect of inclusive leadership on employees’ innovative behavior, challenging the prior linear assumption. Extant research has attempted to explore the impact of inclusive leadership on employees’ innovative behavior, but it has primarily focused on its positive effects (Carmeli et al., 2010), with the potential dark side and nonlinear mechanism lacking in-depth exploration. Building on this, the present study anchors its investigation in Chinese enterprises, situating the research on inclusive leadership within the theoretical framework of the leadership paradox and the TMGT effect. By constructing and validating a double-edged sword model, this study uncovers the nonlinear path through which inclusive leadership influences innovative behavior. The findings reveal that moderate inclusiveness can foster innovative behavior, while excessive inclusiveness leads to innovation inhibition due to factors such as the lack of challenging pressure (Zhu et al., 2020), weakened role authority (Zheng et al., 2018), and dependency in reciprocal relationships (Ma & Tang, 2023). This finding not only responds to the academic call for exploring the dark side of leadership and the potential drawbacks of excessive inclusiveness (Korkmaz et al., 2022; Ma & Tang, 2023; Zheng et al., 2018; Zhu et al., 2020) but also dispels the halo effect of inclusive leadership as conflict-free and purely positive (Zheng et al., 2025). It expands the research perspective from a one-way linear logic to a dialectical nonlinear dynamic balance, providing new empirical support for understanding leadership effectiveness.
Second, this study unlocks the black box of inclusive leadership influencing employees’ innovative behavior, uncovering the intrinsic transmission mechanism of the nonlinear relationship from the perspective of tacit knowledge sharing and responding to scholars’ call for revealing the mediating paths through which leadership styles indirectly drive employees’ innovative behavior (Hughes et al., 2018; Zhang & Zhao, 2024). While existing research has confirmed the mediating role of knowledge sharing between leadership styles and employees’ innovative behavior (Akram et al., 2020), it has focused on explicit knowledge sharing, with insufficient attention paid to tacit knowledge sharing, which is hard-to-codify and highly context-dependent. Drawing on social exchange theory and knowledge creation theory, this study incorporates tacit knowledge sharing as a key mediating variable. The findings reveal that when the level of tacit knowledge sharing exceeds a certain threshold, employees’ innovative behavior tends to diminish due to knowledge overload, cognitive redundancy, and path dependence effects. This helps delineate the boundary of the TMGT effect and provides new theoretical and empirical support for explaining the complex nonlinear relationship between knowledge sharing and innovation performance.
Finally, this study explores the dynamic moderating effect of work tenure, uncovering the differentiated contingency effect of employee tenure differences in the “leadership-innovation” relationship. Extant research has often treated work tenure as a control variable, overlooking its moderating role as an individual characteristic resource. However, existing studies have found that the length of work tenure is a critical variable that influences employee relationships and thus affects their organizational behaviors (Atatsi et al., 2021). Ng and Feldman (2011) demonstrated that employees’ work tenure curvilinearly moderates the relationship between affective commitment and organizational citizenship behavior. Therefore, this study argues that work tenure is not merely a simple contextual factor but rather an important buffer in high-inclusiveness environments, which may influence the effect of inclusive leadership on the relationship between tacit knowledge sharing and employees’ innovative behavior. By incorporating work tenure as a moderating variable, this study reveals the differentiated behavioral patterns exhibited by employees with different tenures under the same leadership style. This finding not only incorporates the temporal dimension into the leadership effectiveness model but also provides a theoretical explanation for understanding differentiated management targeting employees with different tenures in diverse contexts.
Managerial implicationsThe findings of this study offer practical implications for organizational leaders.
First, leaders should recognize the role of inclusive leadership in shaping employees’ innovative behavior while being cautious of its TMGT effect. In management practice, they need to abandon the linear mindset that “more inclusiveness is always better” and instead adopt a principled inclusiveness strategy to establish a dynamic balance between psychological safety and performance constraints. Specifically, leaders should uphold the principle of “the mean”: demonstrating a high level of openness during the idea generation phase to encourage trial and error, while introducing clear accountability mechanisms and challenging goals in the implementation phase to prevent inefficient decision-making or employees’ emotional dependence on leaders caused by excessive tolerance.
Second, given the mediating role of tacit knowledge sharing in driving innovation and its characteristic of diminishing marginal returns, organizations should not merely pursue the frequency of information interaction. Instead, they should strive to optimize the quality and conversion pathways of knowledge governance, constructing a moderate knowledge sharing system to prevent employees’ cognitive overload. Leaders should leverage digital tools to establish classification and filtering mechanisms for core knowledge, thereby reducing the transaction costs of tacit knowledge codification and ensuring that knowledge sharing promotes innovation without occupying excessive cognitive resources.
Finally, managers must emphasize the moderating effect of employee work tenure, abandon the one-size-fits-all management model, and implement seniority-based differentiated contextual management. For new employees, providing high-intensity inclusiveness and emotional support to alleviate their concerns about knowledge sharing is important. For senior employees, however, the model should shift to moderate inclusiveness combined with high empowerment. By granting them greater autonomy and expert status, leaders can stimulate their intrinsic motivation to break free from empiricism and engage in knowledge rumination, thereby achieving precise alignment between leadership styles and employees’ career stage needs.
Limitations and future researchThis study has certain shortcomings and limitations, which need to be improved and refined in subsequent research.
First, this study adopted a cross-sectional research design, with all variables measured through employee self-reports. This limits our ability to draw definitive causal inferences regarding the relationships among the variables. Although we adopted procedural controls and conducted statistical tests to mitigate common method bias, data from a single source may still be influenced by subjective factors. To enhance the robustness of causal conclusions, future research should adopt a longitudinal design or collect multi-source data, include a broader range of employee groups, and use multi-source and multi-wave data to enhance external validity and causal inference power. This approach will more accurately capture the dynamic evolutionary patterns and causal links between variables.
Second, although this study covers different types of enterprises, it does not control over specific industry categories and their potential impacts on innovative behavior. Given that business environments and innovation demands vary across different industries (e.g., high-tech manufacturing and traditional service industries), employees’ innovative behavior likely varies by industry. Consequently, the generalizability of the current findings may be limited in specific industry contexts. Future research can adopt cross-industry comparison or select samples from specific industries to conduct an in-depth investigation into the heterogeneous impacts of inclusive leadership on innovative behavior across different industry contexts, thereby expanding the boundary conditions of the findings.
Third, this study has certain limitations that may affect the generalizability of the conclusions. Although the sample covered regions with different levels of innovation and entrepreneurship activity in China, all data were collected from enterprises in mainland China. This may limit the applicability of the results to other cultural contexts. Additionally, to align with the research theme, participants were restricted to members who frequently engage in knowledge exchange. Their innovation tendency and willingness to share knowledge may be higher than those of average employees. While this helps capture the relationships between variables accurately, it might still lead to sample bias. Future research can extend this work in two directions. First, cross-cultural investigations or incorporating cultural contingencies can validate the generalizability of the proposed model in varying cultural settings. Second, future studies could extend this work by investigating team-level dynamics or incorporate organizational variables as boundary conditions to understand how inclusive leadership influences employee innovation, thereby constructing a more comprehensive, cross-level theoretical framework.
Fourth, although employee self-reported data effectively captures individuals’ subjective perceptions of leadership behaviors, knowledge sharing, and innovative activities, the current design does not establish a true multi-level structure (e.g., multiple subordinates nested under the same leader), thus failing to test cross-level mechanisms. Additionally, while this study has incorporated individual and organizational-level control variables such as organizational innovation climate and job satisfaction to enhance model rigor, it still fails to cover several contextual factors. Particularly key team or organizational-level contextual variables like task interdependence should be incorporated. This omission may limit our comprehensive identification of the boundary conditions of leadership effects. Future research can optimize the sampling strategy by adopting a multilevel survey design and simultaneously collecting contextual data such as task structure and collaboration patterns at the team or department level. By appropriately applying hierarchical linear modelling, future research can more systematically reveal the multi-level mechanisms and contextual dependence of how inclusive leadership influences employee innovative behavior.
ConclusionIn this study, we drew on social exchange theory and knowledge creation theory to examine how inclusive leadership influences employees’ innovative behavior. We found that inclusive leadership exerts an inverted U-shaped impact on employees’ innovative behavior, with tacit knowledge sharing playing a mediating role in this relationship. A moderate inclusive leadership can promote employees’ innovative behavior through tacit knowledge sharing. However, once inclusive leadership exceeds a certain threshold, it will weaken employees’ innovative behavior via tacit knowledge sharing. This study also found that tacit knowledge sharing has an inverted U-shaped impact on employees’ innovative behavior, with moderate tacit knowledge sharing facilitating employees’ innovative behavior. Furthermore, employees’ work tenure plays a moderating role in the relationship. Specifically, it positively moderates the inverted U-shaped relationship between inclusive leadership and employees’ innovative behavior, while negatively moderating the relationship between inclusive leadership and tacit knowledge sharing, thereby weakening both pathways.
Data availabilityThe data presented in this study are available upon request from the corresponding author.
ConfirmationAll authors have agreed to the submission and that the article is not currently being considered for publication by any other journal.
CRediT authorship contribution statementRunping Guo: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Methodology, Funding acquisition, Conceptualization. Kecai Wang: Writing – review & editing, Writing – original draft, Methodology, Data curation. Mengyao Li: Writing – review & editing, Writing – original draft, Investigation. Peng Lu: Writing – review & editing, Writing – original draft, Methodology. Qihan Zhang: Writing – review & editing, Methodology.
The authors declare that they have no competing financial, professional, or personal interests from other parties.
This work was supported by the National Natural Science Foundation of China (NSFC) under Grant [grant number 72572073, grant number 72072069].
