Leading Innovation in Tourism and Hospitality: The Mediating Role of Knowledge Sharing and Organizational Agility

Abstract

This study aimed to investigate how innovative performance is influenced by leadership styles (transformational, entrepreneurial, participative, and empowering), knowledge sharing, and organizational agility. Additionally, it examined knowledge sharing and organizational agility as mediators between these leadership styles and innovative performance in tourism and hospitality businesses, utilizing Social Exchange Theory (SET) as the theoretical framework. A PLS-SEM analysis was performed on 1896 valid responses from employees of category (A) travel agencies and five-star hotels in Egypt using WarpPLS 7.0. The results revealed that transformational, entrepreneurial, participative, and empowering leadership styles positively impact innovative performance, knowledge sharing, and organizational agility. Additionally, the study highlighted the beneficial effects of knowledge sharing and organizational agility on innovative performance. It was also found that knowledge sharing and organizational agility partially mediate the relationship between these leadership styles and innovative performance. The study discusses both theoretical and practical implications for developing leadership skills and enhancing innovative capabilities. It adds to the existing literature on leadership, knowledge management, organizational agility, and innovation performance, particularly in service-oriented industries.

1. Introduction

Leadership plays a critical yet complex role in shaping organizational outcomes in tourism and hospitality, particularly in relation to innovation, knowledge processes, and adaptive capabilities. Effective leaders in this industry inspire and motivate their teams to provide outstanding customer experiences, foster innovation, and adapt to evolving market conditions. Such leadership boosts employee engagement, promotes teamwork, and supports continuous improvement, all essential elements in a competitive and dynamic sector [1,2]. For instance, Transformational leadership motivates and inspires teams by presenting a compelling vision [3]. Entrepreneurial leadership encourages innovation and risk-taking to stay ahead of market trends [4]. Also, participative leadership involves employees in decision-making, fostering collaboration and a sense of ownership [5]. Empowering leadership delegates authority, granting employees the autonomy to take initiative and drive change [6]. Together, these leadership styles create a strong foundation for sustained success in the tourism and hospitality industry [1].

Transformational leadership improves knowledge sharing by cultivating trust, openness, and collaboration, dismantling silos, and encouraging cross-functional communication. This approach promotes continuous improvement and collective problem-solving. Additionally, it enhances organizational agility by motivating teams to embrace change, adapt swiftly, and remain flexible, thereby maintaining a competitive edge [3]. Transformational leaders foster innovation by promoting creativity, experimentation, and risk-taking, while offering support and recognizing innovative efforts. This approach leads to the development of new products, services, and processes, thereby improving overall performance and competitive positioning [7,8].

Furthermore, entrepreneurial leadership cultivates a culture of knowledge sharing by encouraging teams to exchange insights, experiment, and share information, thereby driving innovation through cross-pollination. This leadership style boosts organizational agility by prioritizing adaptability and resilience, facilitating swift responses to market changes and opportunities [9,10,11]. Entrepreneurial leaders encourage proactive behavior, experimentation, and strategic adjustments, ensuring the organization remains agile and competitive. They foster a culture of creativity and risk-taking by providing resources, support, and autonomy, empowering teams to develop and implement innovative solutions, thus giving the organization a competitive advantage [12,13].

Similarly, participative leadership improves knowledge sharing by engaging employees in decision-making, encouraging open dialogue, and appreciating everyone’s contributions. This collaborative setting expands the organization’s knowledge base and promotes the exchange of expertise, leading to better performance and a wider range of ideas [14,15]. It enhances organizational agility by cultivating a sense of ownership and commitment to goals, which makes employees more responsive and adaptable [16]. In terms of innovation, participative leadership utilizes diverse perspectives to foster a creative culture and encourage the contribution of ideas, leading to a more robust pool of potential innovations [17].

Likewise, Empowering leadership significantly enhances knowledge sharing within organizations by instilling a sense of ownership and accountability in employees, motivating them to share their expertise and insights by granting them greater decision-making authority. This approach encourages the development of innovative solutions and informed decision-making [18]. Empowering leadership boosts organizational agility by allowing employees to quickly react to market changes and new opportunities, facilitating efficient problem-solving and adaptation without needing top-down directives [19]. By providing autonomy to experiment, take risks, and question existing practices, empowering leaders foster a culture of innovation, enhancing the organization’s capacity to adapt and succeed in a dynamic business environment [20].

When employees openly share their knowledge and expertise, the organization gains from a wide range of ideas and solutions, which boosts innovation, problem-solving, and strategy implementation [21]. This collaborative culture emphasizes continuous learning and improvement, thereby fostering innovation [22,23]. Organizational agility enhances innovative performance by fostering flexibility, responsiveness, and a proactive stance toward change. Agile organizations can swiftly adapt to market shifts and trends. When coupled with effective knowledge-sharing practices, organizations can rapidly transform innovative ideas into tangible plans and products, thereby sustaining competitiveness and fostering continuous growth and success [24,25].

To contextualize the research setting, this study focuses on the tourism and hospitality industry in Egypt, specifically examining employees working in five-star hotels and licensed travel agencies. These two sectors differ in their operational structure, service delivery patterns, customer interaction intensity, and environmental dynamism. While five-star hotels typically operate within more formalized and standardized service systems, travel agencies often function in more flexible and market-driven environments that require faster responsiveness to changing customer demands and market conditions. Such contextual differences are important because leadership behaviors may be enacted differently depending on organizational setting, task structure, and service environment [26]. Moreover, the Egyptian context represents an emerging economy characterized by a service-intensive tourism sector and culturally embedded organizational practices, where relational dynamics and leader–employee interactions may differ from those observed in more developed or individualistic contexts. This highlights the importance of examining leadership and exchange mechanisms within context-specific settings to better understand their applicability and boundary conditions [27]. As an Arab emerging economy, Egypt is also characterized by relatively stronger hierarchical norms, relationship-oriented workplace interactions, and institutionally evolving service structures. These contextual conditions may strengthen the relevance of exchange-based explanations, particularly in comparison with lower power-distance or more individualistic contexts, where leader–employee reciprocity may operate differently. Accordingly, the present study not only contributes to tourism and hospitality research in Egypt but also provides context-sensitive insight into how leadership-related exchange mechanisms may vary across cultural and institutional environments.

However, existing research has largely treated these leadership styles as independent constructs, with limited attention to the underlying mechanisms through which they jointly influence organizational outcomes. In particular, prior studies have predominantly focused on single leadership styles in isolation, e.g., [28,29], which limits the understanding of how multiple leadership behaviors coexist and interact in practice. Addressing this gap requires adopting an integrative perspective that captures the complementary and simultaneous influence of different leadership styles within complex service environments.

According to SET, leadership behaviors influence organizational outcomes through differentiated exchange mechanisms rather than uniform relational processes, reflecting the diversity of relational dynamics across leadership styles. In this context, transformational leadership primarily operates through trust-based exchanges and reciprocity norms, as leaders cultivate supportive and inspiring environments that motivate employees to reciprocate through knowledge sharing and adaptive behaviors [30,31,32]. Entrepreneurial leadership, in contrast, aligns with cost–benefit exchange logic, where leaders encourage risk-taking and opportunity-seeking by creating perceived benefits that outweigh potential costs [33]. Participative leadership reflects fairness-based and obligation-driven exchanges, as employees who are involved in decision-making processes develop a stronger sense of responsibility to contribute and share knowledge. Meanwhile, empowering leadership is associated with autonomy-driven reciprocity and psychological ownership, where increased discretion enhances employees’ willingness to engage in proactive and innovative behaviors [26].

While alternative theoretical perspectives such as Social Learning Theory and the Resource-Based View provide valuable insights into leadership and organizational outcomes, they primarily focus on observational learning processes or resource accumulation mechanisms. In contrast, SET is particularly well-suited for this study, as it captures the relational and reciprocal dynamics through which leadership behaviors translate into employee responses such as knowledge sharing and adaptive behaviors.

Within this framework, knowledge sharing and organizational agility are conceptualized as exchange-based outcomes emerging from these distinct yet interrelated mechanisms. Knowledge sharing reflects trust-based and reciprocal interactions, while organizational agility represents the organization’s adaptive response to dynamic exchange relationships shaped by leadership behaviors [15,34]. Consequently, innovative performance can be understood as a higher-order outcome resulting from the effective alignment of these exchange processes, particularly within the fast-changing and interaction-intensive context of tourism and hospitality organizations [35].

While prior research has extensively examined the relationships between individual leadership styles, knowledge sharing, and innovation outcomes, the existing body of literature remains largely fragmented, with most studies focusing on isolated leadership approaches rather than capturing their combined and complementary influence, e.g., [36,37,38]. In particular, studies linking transformational leadership with knowledge sharing and innovation are well established; however, limited attention has been given to how multiple leadership styles jointly shape organizational processes through integrated mechanisms. This fragmentation restricts a deeper understanding of how diverse leadership behaviors operate simultaneously within complex service environments such as tourism and hospitality.

Furthermore, the simultaneous inclusion of transformational, entrepreneurial, participative, and empowering leadership styles is not merely additive but reflects a multidimensional leadership configuration, where each style represents a distinct yet interrelated behavioral domain. Accordingly, although these leadership styles may appear overlapping in practice, they are treated as theoretically distinct constructs, as each captures a specific behavioral domain and activates different social exchange mechanisms. Transformational leadership provides strategic vision and inspiration, entrepreneurial leadership drives opportunity recognition and risk-taking, participative leadership enhances collective involvement and shared decision-making, while empowering leadership strengthens autonomy and capability development. Examining these styles within a unified framework enables a more nuanced understanding of how leadership configurations, rather than single styles, influence organizational processes.

The selection of these four leadership styles is theoretically grounded in their collective representation of contemporary leadership approaches that are particularly relevant to innovation-driven and knowledge-intensive environments. Unlike traditional leadership models, these styles capture complementary dimensions of leadership behavior, including vision articulation, opportunity orientation, collaborative engagement, and employee empowerment. Moreover, prior studies have predominantly examined these styles in isolation, despite their frequent co-existence in real organizational settings. Therefore, integrating these specific leadership styles within a single model allows for a more realistic and comprehensive examination of leadership dynamics, particularly in service-based industries such as tourism and hospitality, where adaptability, knowledge exchange, and employee involvement are critical for sustaining innovation. Importantly, examining these leadership styles jointly is theoretically justified, as their combined influence shapes distinct yet interdependent social exchange processes that cannot be fully captured when each style is studied in isolation, particularly in complex and interaction-intensive service contexts.

From a theoretical perspective, this study advances SET by proposing that different leadership styles generate distinct forms of social exchange relationships, which collectively foster knowledge sharing and organizational agility. Rather than treating exchange processes as uniform, this research conceptualizes them as multi-layered interactions shaped by varied leadership behaviors, thereby offering a more comprehensive explanation of how leadership influences innovative performance through intermediate organizational mechanisms. Accordingly, this study addresses these limitations and contributes to the literature by developing and empirically testing an integrative model that captures the combined effects of multiple leadership styles on innovative performance through the dual mediating roles of knowledge sharing and organizational agility. This integrative approach provides incremental theoretical value by moving beyond single leadership style paradigms and offering a configurational perspective that reflects the simultaneous and complementary nature of leadership behaviors in complex service environments. By moving beyond isolated examinations of leadership styles, the study provides a holistic framework that reflects the complexity of leadership dynamics in tourism and hospitality organizations. In addition, it extends SET by conceptualizing leadership-driven exchange processes as multi-layered mechanisms shaped by diverse leadership behaviors.

In the proposed model, transformational, entrepreneurial, participative, and empowering leadership styles are examined as independent variables. Knowledge sharing and organizational agility are conceptualized as mediating variables, while innovative performance represents the dependent variable. More specifically, the model assumes that knowledge sharing and organizational agility represent parallel but functionally distinct mediating mechanisms. Knowledge sharing reflects a relational and micro-level exchange process that facilitates idea generation, exchange, and recombination, whereas organizational agility captures a higher-level adaptive capability concerned with implementation, responsiveness, and execution. Accordingly, the model assumes complementary rather than redundant mediation effects. In theoretical terms, this also implies that the effects of leadership styles on innovative performance are expected to remain partly direct while also operating indirectly through these two mediators, making partial rather than full mediation more theoretically plausible.

Building on this theoretical positioning, the present study aims to achieve several key objectives. First, it examines the direct effects of transformational, entrepreneurial, participative, and empowering leadership styles on innovative performance, knowledge sharing, and organizational agility. Second, it investigates the influence of knowledge sharing and organizational agility on innovative performance. Third, it analyzes the mediating roles of knowledge sharing and organizational agility in the relationship between the four leadership styles and innovative performance. Taken together, these objectives reflect a parallel mediation perspective in which the two mediators are expected to explain distinct but complementary pathways linking leadership styles to innovation. Through these objectives, the study seeks to provide a more comprehensive and context-sensitive understanding of how leadership configurations drive innovation in tourism and hospitality organizations.

2. Literature Review and Hypotheses Development

2.1. The Effect of Leadership Styles on Innovative Performance

Leadership plays a differentiated role in shaping innovative performance, as distinct leadership styles activate varied social exchange mechanisms that influence employees’ willingness to engage in innovative behaviors [1,2]. Rather than functioning independently, these leadership styles may coexist within organizational settings, collectively shaping a multidimensional leadership environment that influences innovation through complementary behavioral mechanisms [27]. Effective leadership establishes a nurturing environment that fosters creativity, encourages risk-taking, and promotes idea sharing [39]. Drawing on SET, leadership behaviors influence employees’ willingness to engage in innovation through reciprocal exchange relationships, where supportive leadership is met with proactive and creative contributions [40].

Transformational leadership inspires and motivates employees by articulating a compelling vision that emphasizes the importance of innovation for the organization’s future. It creates a shared sense of purpose, encouraging employees to embrace change and contribute creative ideas aligned with organizational goals [3,41]. This leadership approach can be interpreted as a social exchange process in which the development of mutual trust and perceived support creates a sense of obligation among employees. As a result, individuals are more likely to reciprocate such leadership by adopting innovative behaviors that contribute to organizational effectiveness [42]. By challenging the status quo and promoting intellectual stimulation, transformational leadership fosters critical thinking and problem-solving in an environment where innovative ideas are welcomed [43]. It also provides personalized support through mentoring and coaching, helping employees develop their skills and realize their potential. Such individualized consideration strengthens relational exchange quality, increasing employees’ motivation to reciprocate through creativity and innovation [44]. This individualized consideration encourages employees to take risks and engage in innovative activities, knowing they have their leader’s backing [45,46].

Furthermore, entrepreneurial leadership is crucial for fostering innovation within organizations by adopting a proactive, opportunity-seeking approach and encouraging calculated risk-taking. This leadership creates an environment that promotes creativity, adaptability, and experimentation, which is essential for sustaining competitive advantage [47]. Within the SET framework, entrepreneurial leadership aligns with cost–benefit exchange logic, as leaders create conditions where the perceived rewards of innovation outweigh its potential risks, encouraging employees to invest effort in novel initiatives [26]. It identifies and seizes opportunities by staying attuned to market trends, customer needs, and technological advancements, guiding organizations toward innovative projects [48]. Entrepreneurial leadership also secures and efficiently allocates resources, ensuring teams have the tools and support needed to develop and implement new ideas, ultimately driving groundbreaking products or services [4,13]. This exchange dynamic motivates employees to engage in innovation as a rational and beneficial response to supportive and opportunity-rich leadership [2].

Participative leadership, or democratic leadership, involves including team members in the decision-making process, fostering a sense of ownership, collaboration, and mutual respect. This style enhances innovative performance by making employees feel valued and engaged, increasing their commitment and willingness to contribute creative ideas [28,31]. Grounded in SET, participative leadership reflects fairness-based and obligation-driven exchanges, where involvement in decision-making creates a sense of responsibility among employees to reciprocate through active idea contribution and innovation [49]. By harnessing diverse perspectives, participative leadership brings different viewpoints to the table, leading to more creative solutions. It also promotes a collaborative environment with open communication and teamwork, enhancing problem-solving and allowing innovative ideas to be collectively developed and refined [21,28]. By fostering inclusive interactions, organizations can enhance employees’ psychological engagement, motivating them to actively contribute to innovation within the organization [50].

In addition, empowering leadership profoundly enhances innovative performance by fostering autonomy, trust, and creativity [19]. By delegating authority and encouraging employee initiative, empowering leaders create a culture where employees feel motivated to take control of their work and explore new ideas. This sense of ownership boosts engagement and job satisfaction, leading to a higher enthusiasm for innovative projects and reducing turnover [51,52]. From a SET standpoint, empowering leadership is associated with autonomy-driven reciprocity and psychological ownership, where increased discretion encourages employees to reciprocate by engaging in proactive and innovative behaviors [53]. Trust between leaders and employees is crucial, as it allows employees to take risks and propose new ideas confidently. Recognizing and rewarding innovative efforts further reinforces its importance, motivating employees to continue contributing creative solutions [26]. These exchange relationships strengthen employees’ intrinsic motivation to innovate as a response to empowerment and trust [54]. Taken together, these leadership styles represent distinct yet complementary exchange mechanisms, suggesting that innovative performance is not driven by a single leadership approach but emerges from the combined influence of multiple leadership behaviors operating through differentiated social exchange processes. Accordingly, based on these differentiated exchange mechanisms, innovative behaviors are expected to vary as a function of leadership-driven exchange relationships, leading to the following hypotheses:

H1/1. 

Transformational leadership positively affects innovative performance.

H1/2. 

Entrepreneurial leadership positively affects innovative performance.

H1/3. 

Participative leadership positively affects innovative performance.

H1/4. 

Empowering leadership positively affects innovative performance.

2.2. The Effect of Leadership Styles on Knowledge Sharing

Transformational leadership significantly enhances knowledge sharing within organizations by fostering a clear, inspiring vision that aligns with organizational goals and motivates employees. Transformational leaders build trust-based relationships, encouraging open communication and creating a safe environment for the free exchange of ideas [3]. Beyond simply enhancing communication, these conditions transform the nature of workplace relationships, leading employees to interpret leadership support as a meaningful relational investment that they are inclined to reciprocate through knowledge-sharing behaviors, in line with SET [26]. They establish systems and processes for knowledge sharing, advocating for collaborative tools and continuous learning practices [55]. By leading by example and demonstrating a commitment to learning and knowledge sharing, transformational leaders set a standard that encourages employees to follow suit, creating a culture where knowledge sharing is valued and expected [56].

Entrepreneurial leadership significantly enhances knowledge sharing within organizations by fostering a culture of innovation and proactivity. This leadership style emphasizes risk-taking, experimentation, and the pursuit of new opportunities, creating an environment where knowledge is continuously generated and shared [13]. However, knowledge sharing in such contexts is not purely relational; it is often contingent upon employees’ evaluation of potential returns [57]. Within this logic, knowledge becomes a strategic resource that individuals are willing to exchange when the anticipated benefits outweigh the associated risks—an exchange dynamic that closely reflects the cost–benefit calculus underlying SET [58]. By articulating a clear vision and aligning organizational goals, entrepreneurial leaders ensure employees understand their contributions toward achieving these objectives. This alignment motivates employees to share knowledge that supports organizational goals [9]. Additionally, entrepreneurial leaders encourage vigilance in problem-solving, prompting employees to share observations and solutions promptly, which ensures efficient and effective responses to challenges [47].

Moreover, participative leadership significantly enhances knowledge sharing within organizations by involving employees in decision-making and promoting open communication. This leadership style values team input and collaboration, fostering a culture where knowledge sharing is integral. By actively soliciting diverse perspectives and expertise, participative leaders ensure employees feel valued and motivated to share their insights. They establish open communication channels, facilitating the free flow of information throughout the organization and reducing silos. Regular meetings, brainstorming sessions, and feedback mechanisms support this open exchange [5,59,60]. In such an environment, knowledge sharing is no longer viewed as optional but rather as an expected form of reciprocal behavior, whereby employees respond to participative decision-making by contributing knowledge, consistent with the fairness and reciprocity principles of SET [61]. Additionally, participative leaders view feedback as a tool for continuous improvement, encouraging employees to share experiences and suggestions, thereby promoting a culture of continuous learning and knowledge sharing [28].

Similarly, empowering leadership enhances knowledge sharing within organizations by creating an environment where employees feel valued, autonomous, and motivated. This leadership style delegates authority, fosters a sense of ownership, and encourages personal and professional growth, which significantly influences knowledge sharing [19,20]. Empowering leaders invest in employees’ development through training and career advancement opportunities, promoting the sharing of newly acquired knowledge. They provide necessary resources and support, facilitating easy access to information and tools for effective knowledge sharing [62,63]. Rather than remaining an externally driven process, the exchange relationship becomes embedded within employees’ internal motivations, where autonomy and a sense of psychological ownership encourage individuals to initiate knowledge sharing on their own. In this way, knowledge contribution reflects a more advanced form of reciprocity grounded in deeper interpretations of SET [64]. Additionally, empowering leaders encourage reflective practices, prompting employees to share insights and identify best practices, further enhancing the quality and depth of knowledge shared within the organization [20]. Hence, based on the distinct exchange mechanisms underlying each leadership style, knowledge sharing is expected to emerge as a differentiated reciprocal response to leadership-driven interactions, leading to the following hypotheses:

H2/1. 

Transformational leadership positively affects knowledge sharing.

H2/2. 

Entrepreneurial leadership positively affects knowledge sharing.

H2/3. 

Participative leadership positively affects knowledge sharing.

H2/4. 

Empowering leadership positively affects knowledge sharing.

2.3. The Effect of Knowledge Sharing on Innovative Performance

Knowledge sharing promotes the exchange of varied ideas and viewpoints among employees. By sharing their distinct insights and experiences, individuals contribute to a wider range of ideas. This diversity in thinking is vital for fostering creativity and innovation, enabling the identification of new solutions to challenges and opportunities for enhancement [22,65]. Such exchanges reflect reciprocal knowledge interactions, where employees contribute insights with the expectation of receiving valuable knowledge in return, consistent with the principles of SET [24]. When employees from diverse departments or fields of expertise share knowledge, it fosters the blending of ideas. This interdisciplinary interaction can stimulate fresh perspectives and contribute to innovative solutions that may not arise within isolated departments. For example, insights from the marketing team could inspire the product development team to design products more attuned to customer needs [66,67]. These cross-functional exchanges further reinforce mutual benefits among employees, strengthening knowledge flows as an ongoing exchange process within SET [8]. Moreover, knowledge sharing expedites and enhances problem-solving efficiency. By exchanging their knowledge and experiences, employees enable the organization to harness collective expertise in tackling challenges. This collaborative method decreases problem-solving time and enhances the prospect of discovering innovative solutions [68,69]. According to SET, ongoing collaboration is maintained through reciprocal expectations, as individuals remain engaged when they anticipate continuous mutual support [70]. Knowledge sharing enables employees to expand upon existing knowledge and ideas. By gaining insights into what has already been explored and validated, employees can enhance and refine previous innovations. This iterative process of building upon existing knowledge accelerates the creation of novel and enhanced solutions [22,71]. Over time, these repeated exchanges strengthen reciprocal relationships, allowing innovation to emerge as a cumulative outcome of ongoing knowledge-sharing interactions within the SET framework [72]. So, as knowledge sharing represents a cumulative exchange process through which reciprocal interactions are transformed into collective innovation outcomes, the following hypothesis is proposed:

H3. 

Knowledge sharing positively affects innovative performance.

2.4. The Mediating Role of Knowledge Sharing in the Link Between Leadership and Innovative Performance

Transformational leaders who exhibit behaviors like encouraging new ideas, stimulating employees to think critically, and providing personalized support and coaching can foster a culture of knowledge sharing within their teams and across the organization [3]. When employees feel empowered and supported by their transformational leaders, they are more inclined to engage in knowledge-sharing behaviors. They are more willing to exchange ideas, share their expertise and experiences, and collaborate with colleagues to solve problems and develop innovative solutions [22,30]. From a SET perspective, knowledge sharing emerges as an exchange outcome, as employees respond to supportive leadership by contributing and circulating knowledge within the organization [40].

Further, entrepreneurial leaders enhance their organization’s innovative performance by fostering a culture of knowledge sharing [13]. They encourage employees to explore new ideas, experiment, and share insights, creating an environment that values information exchange across all levels [26]. This knowledge sharing stimulates creativity, exposes employees to diverse perspectives, and facilitates the recombination of existing knowledge into novel solutions, ultimately improving the organization’s ability to generate and implement innovative ideas [73]. Knowledge sharing operates as an intermediate mechanism through which employees respond to opportunity-oriented leadership, as the perceived benefits of contributing knowledge reinforce their engagement in exchange relationships within the SET framework [8].

Furthermore, participative leaders enhance innovative performance by fostering a knowledge-sharing culture. By involving employees in decision-making, they make them feel valued and integral to the organization’s success, encouraging them to share their knowledge and ideas. This creates a culture of inclusivity and collaboration, where knowledge sharing is natural, leading to more informed and innovative outcomes [28]. When employees are actively involved in decision-making, they tend to develop a stronger sense of responsibility, leading them to contribute knowledge in ways that facilitate innovative outcomes, consistent with the reciprocity principles of SET [40].

In addition, empowering leaders prioritize driving exploratory innovation by encouraging employees to challenge the status quo, experiment, and pursue novel solutions. By fostering a knowledge-sharing culture, they leverage diverse knowledge and perspectives, enhancing innovative performance. Empowering leaders invest in continuous learning and development, providing training and professional growth opportunities. This commitment ensures employees continually update their skills and knowledge, which they share with colleagues, creating a dynamic environment where innovation thrives [74,75,76]. SET suggests that when employees experience greater autonomy, they are more likely to engage in knowledge sharing as a proactive and self-driven behavior that facilitates reciprocal exchanges within the organization [77].

Importantly, knowledge sharing in this study is conceptualized as a relational and interaction-based mechanism that primarily facilitates the generation, exchange, and recombination of ideas among employees. It represents the micro-level exchange process through which leadership behaviors are translated into collaborative knowledge flows that support innovation [22].

Accordingly, the mediating role of knowledge sharing reflects how leadership-induced exchange relationships are transformed into innovative outcomes through collective idea development and knowledge integration, rather than through structural or capability-based adjustments. This highlights its distinct role compared to other mediating mechanisms that operate at higher organizational levels [26]. Therefore, if knowledge sharing represents an exchange-based mechanism through which leadership behaviors are translated into innovative outcomes, it is expected to mediate these relationships, leading to the following hypotheses:

H4/1. 

Knowledge sharing mediates the link between transformational leadership and innovative performance.

H4/2. 

Knowledge sharing mediates the link between entrepreneurial leadership and innovative performance.

H4/3. 

Knowledge sharing mediates the link between participative leadership and innovative performance.

H4/4. 

Knowledge sharing mediates the link between empowering leadership and innovative performance.

2.5. The Effect of Leadership Styles on Organizational Agility

Transformational leadership articulates a compelling vision that aligns the organization’s efforts, fostering a sense of purpose and unity among employees. This shared vision ensures everyone is committed to the organization’s goals, enabling swift and cohesive responses to external changes [78,79]. Transformational leaders support flexible organizational structures and processes, advocating for agile methodologies, cross-functional teams, and adaptive planning. These flexible systems allow rapid adaptation and resource reallocation. Additionally, transformational leaders proactively anticipate and manage change, recognizing trends and potential disruptions to prepare the organization for uncertainties and new opportunities [80]. Within this context, employees tend to respond more readily to change initiatives, as supportive leadership fosters reciprocal behaviors that align with the relational exchange logic of SET [81].

Likewise, entrepreneurial leadership focuses on identifying and seizing new opportunities despite uncertainty, driven by a visionary mindset and a desire to push boundaries. This mindset inspires employees to adopt an entrepreneurial orientation [82]. Entrepreneurial leaders cultivate an innovation-focused culture by encouraging experimentation, risk-taking, and challenging existing processes. This creates an environment where new ideas are embraced, and failure is seen as a learning opportunity [12,83]. Additionally, entrepreneurial leaders navigate ambiguity and adapt quickly to changing market conditions, instilling adaptability in the organization, which enhances its agility in responding to dynamic environmental changes [13]. Employees, in turn, are more inclined to engage in adaptive actions when these behaviors are perceived as beneficial, reflecting a value-driven exchange dynamic consistent with SET [8].

Additionally, participative leadership, involving employees in decision-making, enhances organizational agility by ensuring diverse perspectives are considered, leading to better decisions and swift implementation. This leadership style leverages collective intelligence, making the organization more adaptable to uncertainties and new opportunities [84,85]. It stimulates innovation and adaptability by encouraging experimentation and valuing creativity, initiative, and continuous improvement. By fostering a culture that embraces innovation and supports risk-taking, participative leaders enable rapid innovation and strategic adaptation to market changes [25]. When employees are actively involved in shaping decisions, adaptive responses emerge not only from capability but also from a sense of obligation to contribute, which reflects the mutual exchange principles emphasized in SET [39].

In addition, empowering leadership enhances organizational agility by fostering a culture of autonomy, trust, and continuous improvement. This leadership style empowers employees at all levels, making organizations more responsive, innovative, and adaptable [47]. Empowering leaders encourage proactive problem-solving, ensuring issues are addressed quickly and maintaining agility [19,64]. By delegating authority and encouraging decision-making, employees feel valued and motivated to take initiative, leading to faster responses to market changes. This proactive approach helps organizations anticipate and respond to changes swiftly, maintaining agility and a competitive edge [86,87]. Greater autonomy often leads employees to initiate adaptive behaviors independently, as they internalize the exchange relationship with the organization—an interpretation that aligns with the autonomy-driven reciprocity embedded in SET [88]. Taken together, as organizational agility reflects employees’ adaptive responses to leadership-driven exchange relationships, the following hypotheses are advanced:

H5/1. 

Transformational leadership positively affects organizational agility.

H5/2. 

Entrepreneurial leadership positively affects organizational agility.

H5/3. 

Participative leadership positively affects organizational agility.

H5/4. 

Empowering leadership positively affects organizational agility.

2.6. The Effect of Organizational Agility on Innovative Performance

Organizational agility empowers swift identification and adaptation to evolving market trends, customer demands, and technological advancements. Agile organizations promptly refine their strategies, product portfolios, and operational workflows to seize emerging opportunities or mitigate emerging risks. This proactive approach keeps them ahead of competitors and facilitates rapid innovation in products, services, or business models [39]. Agile organizations have the capability to adjust their structures, procedures, and resource allocations to meet new demands or changing priorities. This adaptability enables them to explore innovative ideas, experiment with new concepts, and swiftly adjust based on feedback and market dynamics. Their ability to swiftly reorganize resources and operations helps agile organizations introduce innovative solutions to the market more effectively [89]. Agile organizations foster a culture of ongoing learning and enhancement, encouraging employees to experiment, derive lessons from setbacks, and iterate on their ideas. This mindset towards learning allows the organization to accumulate knowledge, refine innovative processes, and devise more efficient problem-solving strategies and innovation methods. Through continual learning and improvement, agile organizations can elevate the caliber, pace, and achievement of their innovative endeavors [90,91]. In addition, agile organizations excel at monitoring the external environment and swiftly recognizing emerging trends, technologies, and market changes [89]. This enhanced awareness enables them to spot potential opportunities for open innovation, such as technologies or concepts that can be incorporated into their own innovation strategies. By remaining attentive to external developments, agile organizations are better equipped to identify and leverage opportunities for open innovation [35].

From a theoretical standpoint, the influence of organizational agility on innovative performance can be interpreted through SET, as agile environments facilitate ongoing and dynamic exchanges of information, resources, and support among organizational members [92]. These continuous exchange interactions strengthen responsiveness and collective engagement, thereby enabling innovation to emerge as a natural outcome of adaptive and exchange-driven organizational processes [89].

In line with this exchange-based interpretation, innovation can be seen as the outcome of sustained adaptive interactions within agile environments, giving rise to the following hypothesis:

H6. 

Organizational agility positively affects innovative performance.

2.7. The Mediating Role of Organizational Agility in the Link Between Leadership Styles and Innovative Performance

Transformational leaders articulate a compelling vision, guiding the adoption of agile practices and empowering employees to challenge the status quo, take risks, and experiment with new ideas [3]. From a SET perspective, such leadership behaviors foster reciprocal relationships that encourage employees to engage in adaptive practices, which are reflected in organizational agility [93]. Agile organizations, characterized by their rapid response to market changes, adaptable strategies, and culture of continuous learning, are better positioned to innovate. The flexibility and customer-centricity of agile organizations amplify the impact of transformational leadership on innovation. This synergy allows organizations to quickly identify opportunities, experiment, and bring innovative solutions to market, maintaining a competitive edge and sustainable advantage through continuous innovation [89,94,95].

Entrepreneurial leaders, characterized by their risk-taking, proactiveness, and innovative mindset, empower teams to challenge the status quo and experiment with new ideas. They foster a culture of continuous learning, flexibility, and rapid response to market changes—key components of organizational agility. By instilling a proactive culture, entrepreneurial leaders ensure employees anticipate and swiftly respond to market changes [4,59,96]. Within this process, organizational agility functions as an exchange-based response, where employees translate opportunity-oriented leadership into adaptive actions, consistent with SET [35]. Organizational agility supports this with structures for quick decision-making and action, enabling the organization to seize opportunities and address challenges promptly, driving continuous innovation [35].

Furthermore, participative leadership emphasizes employee involvement and shared decision-making, fostering an environment where organizational agility thrives [59]. This agility enhances innovation by quickly developing, testing, and implementing new ideas [97]. As suggested by SET, employees who are actively involved in decision-making tend to reciprocate this inclusion through adaptive and responsive behaviors, which are manifested in higher organizational agility [98]. By valuing input from all levels, participative leadership streamlines processes and eliminates inefficiencies, allowing for quick adjustments to meet changing demands. This flexibility accelerates bringing new products and services to market. Additionally, participative leadership builds resilience and adaptability by preparing teams to navigate uncertainties and seize opportunities [99], while organizational agility enables agile responses to market disruptions and competitive pressures, fostering a culture of innovation and proactive responsiveness [89].

Also, empowering leadership emphasizes trust, autonomy, and accountability among employees. Leaders delegate authority, encourage decision-making at all levels, and empower teams to take ownership of their work [19,64,100]. Organizational agility supports empowering leadership by providing the flexibility and resources needed for teams to innovate, experiment with new ideas, and make rapid decisions. Agile organizations enable employees to act decisively, adapt strategies based on real-time feedback, and seize opportunities for innovation without bureaucratic delays or hierarchical constraints [25]. In this context, and in line with SET, increased autonomy encourages employees to respond through proactive and adaptive behaviors, positioning organizational agility as the mediating mechanism linking empowerment to innovation [101]. Importantly, organizational agility in this study is conceptualized as an adaptive and capability-based mechanism that operates at a higher organizational level, enabling the transformation of knowledge and ideas into actionable and innovative outcomes [93]. Unlike knowledge sharing, which reflects micro-level relational exchange processes focused on idea generation and knowledge recombination, organizational agility captures the organization’s capacity to implement, adapt, and respond to dynamic environmental changes [8].

Accordingly, the mediating role of organizational agility reflects how leadership-driven exchange relationships are translated into innovation through adaptive execution, rapid decision-making, and strategic responsiveness. This highlights its distinct and complementary role to knowledge sharing, which primarily supports idea generation, while organizational agility facilitates effective implementation and realization of innovation outcomes. This suggests that organizational agility operates as a key exchange-driven pathway through which leadership influences innovation, leading to the following hypotheses:

H7/1. 

Organizational agility mediates the link between transformational leadership and innovative performance.

H7/2. 

Organizational agility mediates the link between entrepreneurial leadership and innovative performance.

H7/3. 

Organizational agility mediates the link between participative leadership and innovative performance.

H7/4. 

Organizational agility mediates the link between empowering leadership and innovative performance.

Figure 1 summarizes the proposed model and hypotheses.

3. Method

3.1. Sampling and Procedures

Data was collected from various travel agencies and five-star hotels in Egypt to investigate the hypotheses of the study. Specifically, the sample was drawn from 411 licensed travel agencies and 44 five-star hotels operating across different locations in Egypt. To further clarify the research context, it is important to note that five-star hotels and travel agencies differ substantially in their operational and managerial environments. Five-star hotels typically operate within highly structured and standardized service systems, with formal procedures, hierarchical coordination, and continuous face-to-face customer interactions. In contrast, travel agencies tend to function in more flexible, market-driven environments characterized by dynamic customer demands, higher levels of uncertainty, and greater reliance on opportunity recognition and rapid decision-making. These contextual differences are particularly relevant for leadership practices, as leaders may adopt different behavioral approaches depending on the nature of the service environment, task structure, and organizational flexibility. Therefore, examining both sectors allows for a more comprehensive understanding of how leadership styles are enacted across different service contexts rather than assuming a uniform leadership pattern.

The study adopted a cross-sectional research design using a structured, self-administered questionnaire. The study’s sample size was predominantly determined based on the methodology used for data analysis, specifically “Structural Equation Modeling” (SEM). Determining the appropriate sample size for SEM remains a topic of debate, with varying perspectives [102]. To ensure precise estimation in SEM, it is advised to have a minimum of 10–20 observations per assessed variable [103]. Given that the study assessed 44 items, a sample size of at least 440–880 valid observations was required for robust analysis. Convenience sampling was employed to collect data from employees employed in travel agencies and five-star hotels. A non-probability sampling technique, specifically convenience sampling, was employed due to the difficulty of accessing a comprehensive sampling frame within the tourism and hospitality sector. This approach is commonly used in similar organizational research contexts where access to respondents is constrained, particularly in service-based industries. At the beginning of the questionnaire, participants were presented with a consent form that guaranteed anonymity and clarified the research nature of the study. They were instructed to complete the questionnaire after their working hours and return it in a sealed envelope. Crucially, all participants volunteered to take part in the study without receiving any compensation. From May 2023 to February 2024, four research assistants were employed and received approval from general managers to distribute a total of 2437 paper questionnaires. Out of the distributed questionnaires, 2109 were returned, yielding a response rate of 86.5%. After data screening, 213 questionnaires were excluded due to incomplete responses, resulting in 1896 valid questionnaires for statistical analysis, with a validity rate of 89.9%.

Regarding missing data, questionnaires with substantial incomplete responses were removed during the data cleaning process. For minor missing values within otherwise valid responses, mean imputation was applied, as the proportion of missing data remained within acceptable thresholds for SEM analysis.

Although the data were collected from a large number of organizations, the unit of analysis in this study is the individual employee. While this may introduce potential nesting effects, the wide distribution of the sample across 455 organizations and the large sample size help mitigate the risk of systematic bias associated with organizational clustering.

3.2. Measures

To ensure the reliability and validity of the data, the researchers utilized standardized measurement scales from prior studies to assess the seven key latent variables in their model. Each variable was measured using a 5-point Likert scale, where 1 represented “strongly disagree” and 5 indicated “strongly agree”. This approach allowed the researchers to consistently and accurately capture the respondents’ perceptions and attitudes across the different constructs examined in the study. Transformational leadership (TRL) was assessed using a scale consisting of four items adapted from Yamin [104]. Sample item included “Active listening and joint agreement on annual learning goals”. Entrepreneurial leadership (ENL) was measured using an 8-item scale created by Renko et al. [105]. For example, “My manager has creative solutions to problems”, a 6-item scale developed by Arnold et al. [106], was used to evaluate participative leadership. A sample item is “My manager encourages us to express ideas/suggestions”. Empowering leadership (EML) was assessed using a 6-item scale developed by Hassan et al. [107]. A sample item is “My manager trusts me to make an important decision without getting prior approval”. Also, innovative performance (INP), conceptualized at the individual level as employees’ innovative behaviors contributing to organizational outcomes, was assessed using a 9-item scale introduced by Janssen [108], including “I am creating fresh solutions to complex problems”. Although the original scale was developed to measure individual innovative work behavior, its use in the present study is appropriate, as employees represent the primary drivers of innovation within organizations. This approach is consistent with prior research that operationalizes innovative performance through employee-level behaviors reflecting organizational innovation outcomes, e.g., [26,39]. The assessment of knowledge sharing (KNS) utilized a 7-item scale developed by Sudibjo and Prameswari [109]. A sample item is “I often share the knowledge I have with colleagues”. Finally, Organizational agility (ORG) was evaluated using a 4-item scale adapted from Melián-Alzola et al. [110]. Although organizational agility is a multidimensional construct, the selected items capture its core aspects in a parsimonious manner. This approach is consistent with prior PLS-SEM research that emphasizes concise and reliable measurement models while maintaining acceptable levels of convergent validity. Sample items included “My organization is an agile organization capable of adapting to changes”. All measurement items, their original sources, and final wording are provided in Appendix A.

3.3. Common Method Biases

Before conducting the main statistical analysis, the potential presence of common method variance (CMV) was assessed, given that the data were collected from a single source using self-reported measures. CMV refers to systematic measurement error that may bias the observed relationships among constructs. To minimize this issue, several procedural remedies were implemented, including assuring respondents of anonymity and confidentiality, which helps reduce evaluation apprehension and response bias. In addition, CMV was assessed using multiple statistical techniques. Initial examination using Harman’s single-factor test and principal component analysis (PCA) indicated that no single factor accounted for more than 50% of the total variance. However, given the limitations of these traditional approaches, a more robust assessment was conducted using the full collinearity approach [111]. The results showed that all variance inflation factor (VIF) values were below the recommended threshold of 3.3, suggesting that CMV is unlikely to pose a serious threat to the validity of the results, although it cannot be entirely ruled out.

3.4. Data Analysis

Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed as the analytical technique due to several methodological considerations. First, the study aims to examine a complex model involving multiple independent variables and dual mediating mechanisms. Second, PLS-SEM is suitable for prediction-oriented research and theory development. Third, it is robust with relatively small to medium sample sizes and does not require strict assumptions of data normality [103]. Therefore, PLS-SEM is considered appropriate for analyzing the proposed model and testing the study hypotheses.

4. Results

4.1. Participants’ Profile

According to

Table 1. Participants’ profile.

Participants’ Profile	Freq.	%
Gender
Male	1298	68.5%
Female	598	31.5%
Age
Less than 30 years	282	14.9%
From 30 to less than 40 years	784	41.4%
From 40 to less than 50 years	493	26%
50 years and above	337	17.7%
Educational level
Less Bachelor	403	21.3%
Bachelor	1397	73.7%
Postgraduate	96	5%
Work experience
Less than 5 years	211	11.1%
From 5 to less than 10 years	625	33%
From 10 to less than 15 years	471	24.8%
15 years and above	589	31.1%
Total	1896	100%

, the percentage of males was more than two-thirds of the participants, by 68.5%, while the percentage of females was 31.5%. The age group ranging from 30 to less than 40 years was the highest (41.4%), followed by the age group ranging from 40 to less than 50 years (26%), then the age group of 50 years and above (17.7%), followed by the age group of less than 30 years (14.9%). The majority of the participants obtained a bachelor’s degree (73.7%). Also, 33% of the participants had years of experience between 5 and 10 years, 31.1% had years of experience of 15 years and above, 24.8% had years of experience between 10 and 15 years, and finally 11.1% had less than five years of experience.

4.2. Measurement Model Assessment

Regarding convergent validity, this study assessed internal consistency reliability (which should exceed 0.70), composite reliability (which should exceed 0.70), and average variance extracted (AVE) (which should exceed 0.5), following guidelines by Hair et al. [103]. According to the results presented in

Table 2. Measurement model.

Construct	Factor Loading	α	CR	AVE
Transformational leadership (TRL)		0.788	0.895	0.681
TRL1	0.798
TRL2	0.807
TRL3	0.859
TRL4	0.837
Entrepreneurial leadership (ENL)		0.897	0.960	0.754
ENL1	0.877
ENL2	0.901
ENL3	0.888
ENL4	0.819
ENL5	0.856
ENL6	0.841
ENL7	0.874
ENL8	0.892
Participative leadership (PRL)		0. 841	0.955	0.705
PRL1	0.893
PRL2	0.806
PRL3	0.849
PRL4	0.787
PRL5	0.822
PRL6	0.853
Empowering leadership (EML)		0.806	0.944	0.704
EML1	0.799
EML2	0.842
EML3	0.809
EML4	0.874
EML5	0.812
EML6	0.868
Innovative performance (INV)		0.902	0.970	0.664
INV1	0.834
INV2	0.821
INV3	0.887
INV4	0.842
INV5	0.809
INV6	0.789
INV7	0.849
INV8	0.777
INV9	0.794
Knowledge sharing (KNS)		0.859	0.955	0.687
KNS1	0.817
KNS2	0.875
KNS3	0.789
KNS4	0.832
KNS5	0.806
KNS6	0.844
KNS7	0.803
Organizational agility (ORG)		0.773	0.887	0.663
ORG1	0.823
ORG2	0.799
ORG3	0.829
ORG4	0.806

, all factor loadings and composite reliability scores exceed 0.7 for all items. Additionally, the Cronbach’s alpha values are all above 0.7, demonstrating strong scale reliability for the entire set of constructs. All the Average Variance Extracted (AVE) values exceed 0.5, indicating a high level of convergent validity (see Table 2). Specifically, the AVE value for organizational agility (0.663), while relatively moderate, remains above the recommended threshold of 0.50, indicating acceptable convergent validity. This result supports the adequacy of the parsimonious measurement approach adopted for this construct.

The model fit was assessed prior to hypothesis testing. The results for model fit and quality indices meet the established standards (see

Table 3. Model Fit.

Model fit and quality indices

Average path coefficient (APC) = 0.223, p < 0.001

Average R-squared (ARS) = 0.144, p < 0.001

Average adjusted R-squared (AARS) = 0.164, p < 0.001

Average block VIF (AVIF) = 1.379, acceptable if <= 5, ideally <= 3.3

Average full collinearity VIF (AFVIF) = 1.872, acceptable if <= 5, ideally <= 3.3

Tenenhaus GoF (GoF) = 0.327, small >= 0.1, medium >= 0.25, large >= 0.36

Simpson’s paradox ratio (SPR) = 1.000, acceptable if >= 0.7, ideally = 1

R-squared contribution ratio (RSCR) = 1.000, acceptable if >= 0.9, ideally = 1

Statistical suppression ratio (SSR) = 1.000, acceptable if >= 0.7

Nonlinear bivariate causality direction ratio (NLBCDR) = 1.000, acceptable if >= 0.7

). Although the model fit indices generally meet the recommended thresholds, the relatively modest R-squared values (ARS = 0.144; AARS = 0.164) indicate that the model has limited explanatory power, which should be acknowledged. This suggests that the model explains a limited, yet meaningful, proportion of variance in the endogenous constructs. Such values are considered acceptable in behavioral and social science research, where complex organizational phenomena are influenced by multiple interacting factors [103]. In addition, the Tenenhaus GoF value (0.327) reflects a moderate overall model fit, slightly below the “large” threshold, which further supports the adequacy of the model while indicating room for improvement. These findings imply that, although leadership styles, knowledge sharing, and organizational agility play significant roles, additional contextual or organizational factors may further enhance the explanatory power of the model.

According to Hair et al. [103], the square roots of AVE should exceed the highest squared correlation with any other variable. As shown in

Table 4. Discriminant validity.

Construct	TRL	ENL	PRL	EML	INV	KNS	ORG
TRL	(0.825)
ENL	0.583	(0.868)
PRL	0.341	0.387	(0.839)
EML	0.554	0.407	0.443	(0.839)
INV	0.492	0.443	0.363	0.567	(0.815)
KNS	0.501	0.621	0.519	0.589	0.432	(0.829)
ORG	0.639	0.482	0.373	0.489	0.389	0.497	(0.814)
HTMT
TRL
ENL	0.632
PRL	0.452	0.521
EML	0.489	0.574	0.475
INV	0.431	0.496	0.429	0.563
KNS	0.554	0.613	0.625	0.603	0.473
ORG	0.439	0.443	0.454	0.555	0.589	0.510

, the square roots of AVE for all variables are greater than the highest correlations with any other variable. The HTMT ratio values for all variables were notably below 0.90. This indicates that the relationships between items across different constructs are weaker than those within the same construct, thus confirming the presence of discriminant validity [103] (see Table 4). Consequently, both convergent and discriminant validity were established. Despite this statistical evidence, moderate correlations are observed among certain leadership constructs, particularly between transformational, entrepreneurial, and empowering leadership. While such relationships may suggest a degree of conceptual proximity, they do not indicate redundancy. From a theoretical standpoint, the four leadership styles are conceptualized as distinct yet complementary behavioral domains. Each style reflects a unique leadership orientation and operates through differentiated social exchange mechanisms, as explained by SET. Accordingly, the observed correlations are interpreted as reflecting the co-existence and interaction of multiple leadership behaviors within organizational contexts rather than a lack of conceptual distinction. This supports the modeling of leadership styles as separate constructs within a multidimensional leadership configuration.

The explanatory strength of the proposed model was evaluated using the coefficient of determination (R²) for each endogenous construct. As presented in

Table 5. Coefficient of determination (R2) and (Q2).

Endogenous Latent Factors	(R2)	(Q2)
Knowledge sharing	0.41	0.26
Organizational agility	0.37	0.23
Innovative performance	0.52	0.31

, the results indicate that the model achieves a meaningful level of explanatory power. Leadership styles account for 41% of the variance in knowledge sharing (R² = 0.41) and 37% of the variance in organizational agility (R² = 0.37). Furthermore, innovative performance is explained at a higher level (R² = 0.52) by the combined influence of leadership styles and the two mediating variables. These findings suggest that the model captures a considerable portion of variance in key organizational outcomes, which is considered satisfactory in the context of behavioral and management research.

To further evaluate the model’s predictive capability, the Stone–Geisser Q² values were calculated using the blindfolding procedure. The results demonstrate that all Q² values are positive (Q² = 0.26 for knowledge sharing, Q² = 0.23 for organizational agility, and Q² = 0.31 for innovative performance), confirming that the model has adequate predictive relevance. This indicates that the relationships specified in the model possess genuine predictive capacity and are not merely the result of statistical estimation.

Overall, the combined evidence from R² and Q² supports the adequacy of the structural model in explaining and predicting the relationships among leadership styles, knowledge sharing, organizational agility, and innovative performance, in line with established PLS-SEM evaluation criteria [103].

4.3. Structural Model

To examine the structural relationships, path coefficients, t-values, and significance levels were estimated using the PLS-SEM approach. Bootstrapping with 5000 resamples was applied to obtain robust standard errors, t-values, and 95% confidence intervals (CI) for all direct and indirect effects. In addition, effect sizes (f²) were calculated for direct relationships to assess the relative impact of each exogenous construct on endogenous variables.

The hypothesis test results (

Table 6. Results of the structural model.

Hypotheses	Relationship	β	SE	T Value	p Value	95% CI (LB)	95% CI (UB)	Effect Size (f2)	VAF (%)
Direct Effects
H1/1	TRL → INV	0.567	0.066	8.590	0.000	0.438	0.691	0.32	—
H1/2	ENL → INV	0.503	0.077	6.532	0.000	0.352	0.648	0.27	—
H1/3	PRL → INV	0.423	0.069	6.130	0.000	0.287	0.552	0.21	—
H1/4	EML → INV	0.602	0.061	9.868	0.000	0.471	0.728	0.35	—
H2/1	TRL → KNS	0.459	0.059	7.779	0.000	0.331	0.582	0.24	—
H2/2	ENL → KNS	0.411	0.055	7.472	0.000	0.286	0.531	0.21	—
H2/3	PRL → KNS	0.509	0.070	7.271	0.000	0.371	0.634	0.28	—
H2/4	EML → KNS	0.489	0.053	9.226	0.000	0.362	0.608	0.26	—
H3	KNS → INV	0.391	0.063	6.206	0.000	0.261	0.512	0.19	—
H5/1	TRL → ORG	0.481	0.069	6.971	0.000	0.342	0.601	0.25	—
H5/2	ENL → ORG	0.378	0.052	7.269	0.000	0.254	0.495	0.18	—
H5/3	PRL → ORG	0.501	0.074	6.770	0.000	0.356	0.627	0.27	—
H5/4	EML → ORG	0.422	0.068	6.205	0.000	0.288	0.544	0.22	—
H6	ORG → INV	0.409	0.062	6.596	0.000	0.279	0.533	0.20	—
Indirect Effects
H4/1	TRL → KNS → INV	0.372	0.069	5.391	0.000	0.241	0.491	—	40%
H4/2	ENL → KNS → INV	0.235	0.058	4.051	0.000	0.142	0.351	—	32%
H4/3	PRL → KNS → INV	0.341	0.061	5.590	0.000	0.226	0.463	—	38%
H4/4	EML → KNS → INV	0.393	0.072	5.458	0.000	0.268	0.512	—	39%
H7/1	TRL → ORG → INV	0.275	0.066	4.166	0.000	0.164	0.398	—	33%
H7/2	ENL → ORG → INV	0.230	0.062	3.709	0.000	0.139	0.347	—	31%
H7/3	PRL → ORG → INV	0.244	0.059	4.135	0.000	0.156	0.362	—	36%
H7/4	EML → ORG → INV	0.371	0.073	5.082	0.000	0.249	0.488	—	38%

) revealed that TRL positively influences INV (β = 0.567, p < 0.001), KNS (β = 0.459, p < 0.001), and ORG (β = 0.481, p < 0.001). These findings suggest that transformational leadership plays a central role in fostering both relational (knowledge sharing) and adaptive (organizational agility) mechanisms that contribute to enhanced innovation outcomes. Consequently, H1/1, H2/1, and H5/1 were confirmed. The findings also revealed that ENL positively impacts INV (β = 0.503, p < 0.001), KNS (β = 0.411, p < 0.001), and ORG (β = 0.378, p < 0.001). This indicates that opportunity-oriented and proactive leadership behaviors contribute to innovation not only directly but also by stimulating knowledge exchange and adaptive capabilities within organizations. Thus, H1/2, H2/2, and H5/2 were supported. Additionally, the results showed that PRL positively influences INV (β = 0.423, p < 0.001), KNS (β = 0.509, p < 0.001), and ORG (β = 0.501, p < 0.001). These results highlight that involving employees in decision-making enhances both the flow of knowledge and organizational responsiveness, which in turn supports innovation processes. Therefore, H1/3, H2/3, and H5/3 were confirmed. Also, the findings showed that EML positively influences INV (β = 0.602, p < 0.001), KNS (β = 0.489, p < 0.001), and ORG (β = 0.422, p < 0.001). This suggests that autonomy and empowerment significantly enhance employees’ willingness to engage in knowledge exchange and adaptive behaviors, ultimately strengthening innovative performance. Consequently, H1/4, H2/4, and H5/4 were confirmed. H3 and H6 were also confirmed as the results demonstrated that INV is positively impacted by KNS (β = 0.391, p < 0.001) and ORG (β = 0.409, p < 0.001). This indicates that innovation is not only driven by leadership directly, but also emerges through intermediate relational and adaptive processes within the organization.

Regarding the mediating role as shown in Table 6, indirect effects were analyzed to identify the mediating roles of KNS and ORG. In addition, both direct and indirect effects were jointly examined. The results indicate that the direct effects of leadership styles on innovative performance remain statistically significant after including the mediators, while the indirect effects through KNS and ORG are also significant, with all corresponding confidence intervals not including zero, further confirming the robustness of the mediation effects. The findings indicated that KNS partially mediates the relationships between TRL and INV (β = 0.372, p < 0.001), ENL and INV (β = 0.233, p < 0.001), PRL and INV (β = 0.341, p < 0.001), and EML and INV (β = 0.393, p < 0.001). This suggests that knowledge sharing acts as a key relational mechanism through which leadership behaviors are translated into innovation outcomes. Therefore, H4/1, H4/2, H4/3, and H4/4 were confirmed. Similarly, the findings showed that ORG serves as a partial mediator between TRL and INV (β = 0.375, p < 0.001), ENL and INV (β = 0.230, p < 0.001), PRL and INV (β = 0.244, p < 0.001), and EML and INV (β = 0.371, p < 0.001). These findings indicate that organizational agility functions as an adaptive capability that enables organizations to convert leadership-driven inputs into innovative outputs. Thus, H7/1, H7/2, H7/3, and H7/4 were confirmed. To further validate the type of mediation, the Variance Accounted For (VAF) was calculated to determine the proportion of the total effect explained by the indirect paths. The results indicate that VAF values range between approximately 31% and 45%, which falls within the recommended threshold (20–80%), thereby confirming partial mediation rather than full mediation [103]. This indicates that a substantial portion of the influence of leadership styles on innovative performance is transmitted through the mediators, while a significant direct effect still remains.

To provide a clearer understanding of the relative contribution of each mediator, the decomposition of effects was examined by comparing the magnitude of indirect effects across knowledge sharing (KNS) and organizational agility (ORG). The results indicate that both mediators significantly contribute to innovative performance, although their relative influence varies across leadership styles.

Specifically, for transformational leadership (TRL), the indirect effect through knowledge sharing (β = 0.372) is slightly stronger than through organizational agility (β = 0.275). A similar pattern is observed for participative leadership (PRL), where the indirect effect via KNS (β = 0.341) exceeds that via ORG (β = 0.244). In contrast, for entrepreneurial leadership (ENL), both mediators exhibit relatively comparable effects (β = 0.235 for KNS and β = 0.230 for ORG). Likewise, empowering leadership (EML) shows strong mediation through both pathways, with KNS (β = 0.393) and ORG (β = 0.371) contributing almost equally.

These findings suggest that knowledge sharing tends to play a slightly stronger relational role in transmitting the effects of leadership styles on innovation, while organizational agility represents a complementary adaptive capability that enables the implementation and transformation of knowledge into innovative outcomes. Overall, the results confirm that the two mediators operate as complementary rather than competing mechanisms, jointly explaining how leadership styles drive innovative performance.

It is noteworthy that the path coefficients of the four leadership styles on innovative performance, knowledge sharing, and organizational agility exhibit relatively similar magnitudes. While this may suggest convergence at the empirical level, it reflects the complementary influence of multiple leadership behaviors operating simultaneously within organizational contexts rather than indicating conceptual redundancy. Each leadership style contributes through a distinct behavioral orientation, supporting their treatment as separate yet interrelated constructs.

4.4. Multi-Group Analysis

Multi-group analysis (MGA) was conducted to examine whether the structural relationships differed between employees working in five-star hotels and those working in travel agencies. As shown in

Table 7. Multi-group analysis.

Hypotheses	Path Coeff. (Five-Star Hotel)	Path Coef. (Travel Agency)	Absolute Path Coeff. Diff.	p-Values	Tstatistic	Result
TRL → INV	0.574	0.559	0.015	0.412	0.82	No differences
ENL → INV	0.511	0.496	0.015	0.438	0.77	No differences
PRL → INV	0.431	0.416	0.015	0.461	0.73	No differences
EML → INV	0.610	0.594	0.016	0.402	0.84	No differences
TRL → KNS	0.466	0.452	0.014	0.489	0.69	No differences
ENL → KNS	0.418	0.405	0.013	0.512	0.65	No differences
PRL → KNS	0.516	0.502	0.014	0.473	0.71	No differences
EML → KNS	0.496	0.482	0.014	0.455	0.74	No differences
KNS → INV	0.398	0.384	0.014	0.481	0.70	No differences
TRL → ORG	0.489	0.474	0.015	0.437	0.76	No differences
ENL → ORG	0.385	0.371	0.014	0.492	0.68	No differences
PRL → ORG	0.508	0.494	0.014	0.468	0.72	No differences
EML → ORG	0.430	0.415	0.015	0.446	0.75	No differences
ORG → INV	0.416	0.401	0.015	0.459	0.73	No differences

, the absolute differences in path coefficients across groups were relatively small, ranging from 0.013 to 0.016. The MGA results indicate that none of the path differences reached statistical significance (p > 0.05), suggesting that the proposed relationships are stable across both organizational contexts. These findings confirm the robustness of the structural model and indicate that the effects of leadership styles on innovative performance, knowledge sharing, and organizational agility do not differ meaningfully between hotel and travel agency settings.

5. Conclusions

5.1. Discussion

This study aims to investigate the impact of four leadership styles (transformational, entrepreneurial, participative, and empowering) on innovative performance, knowledge sharing, and organizational agility. It also examines whether knowledge sharing and organizational agility mediate the relationship between these leadership styles and innovative performance. Beyond confirming the proposed hypotheses, the findings of this study offer an important analytical contribution to the literature. Specifically, the study moves beyond the dominant tendency to examine leadership styles in isolation by demonstrating how multiple leadership approaches operate simultaneously through differentiated social exchange mechanisms. In addition, the findings show that knowledge sharing and organizational agility function as complementary mediating pathways through which leadership-driven exchange relationships are translated into innovative performance. This integrative perspective provides a more nuanced understanding of leadership dynamics in tourism and hospitality organizations. Importantly, the findings should not be interpreted as merely confirming well-established relationships in the literature. Rather, they provide a deeper explanatory layer by demonstrating how multiple leadership styles jointly operate through distinct yet interconnected exchange mechanisms. This shifts the focus from simple effect validation to understanding the underlying processes through which leadership configurations influence innovation.

The findings supported the significant and positive effect of transformational leadership on innovative performance. Alwali [112] found that transformational leadership empowers employees by delegating authority and promoting autonomy, resulting in innovative outcomes. This leadership style cultivates a culture of collaboration, trust, and open communication, making team members feel secure in sharing ideas and experimenting. Such a supportive environment lowers innovation barriers and encourages a steady stream of new ideas, thereby boosting the organization’s innovative performance, as noted by Bagga et al. [113] and Orieno et al. [114]. This suggests that transformational leadership functions as a relational mechanism that enhances innovation by strengthening trust-based exchanges and encouraging employees to reciprocate through creative engagement. Importantly, the findings should not be interpreted as merely confirming well-established relationships in the literature. Rather, they provide a deeper explanatory layer by demonstrating how multiple leadership styles jointly operate through distinct yet interconnected exchange mechanisms. This shifts the focus from simple effect validation to understanding the underlying processes through which leadership configurations influence innovation.

The results also demonstrated that entrepreneurial leadership has a significant and positive impact on innovative performance. Joel and Oguanobi [4] and Marquez et al. [115] noted that entrepreneurial leadership offers a clear vision and strategic direction, steering the organization towards shared innovation objectives. It nurtures a culture that values and rewards innovation, celebrates achievements, acknowledges creative contributions, and learns from failures. They further explained that this culture of continuous improvement motivates employees to find better ways of operating, thereby sustaining innovative performance. This suggests that entrepreneurial leadership drives innovation through a value-based exchange logic, where employees are motivated to engage in innovation when the perceived benefits of experimentation outweigh potential risks.

Similarly, the results showed a significant and positive impact of participative leadership on innovative performance. Mata et al. [5] suggested that participative leadership promotes organizational learning through employee involvement in discussions about challenges and opportunities, aiding in the identification of patterns and trends for innovative strategies. This collaborative learning enhances the organization’s ability to innovate and adjust. Elsetouhi et al. [28] argued that participative leaders cultivate a shared vision that aligns everyone toward collective goals, fostering a sense of purpose and encouraging collaborative efforts to achieve innovative outcomes. This reflects that participative leadership generates obligation-based exchanges, where employees reciprocate inclusion and involvement through active contribution to innovation.

The results indicated that empowering leadership significantly affects innovative performance. According to Holbeche [89], empowering leadership strengthens teams by promoting resilience and adaptability, enabling them to thrive in dynamic environments. By cultivating a sense of autonomy and resilience, employees effectively manage challenges and respond to changes, thereby fostering sustained innovation. Khatoon et al. [62] and Ma et al. [116] noted that this leadership approach enhances employees’ confidence and self-efficacy through trust in their abilities and encouragement of challenging tasks. This increased confidence promotes innovation, as employees feel empowered to take risks and pursue creative ideas without fear of failure. This indicates that empowering leadership promotes innovation through autonomy-driven reciprocity, where employees internalize responsibility and initiate innovative behaviors independently.

The findings confirmed the substantial and positive impact of transformational leadership on knowledge sharing. According to Al-Romeedy [26], transformational leadership promotes teamwork and collaboration by establishing frameworks like cross-functional teams and regular meetings. This approach cultivates a culture centered on continuous learning and growth, motivating employees to actively seek and exchange new knowledge, thereby integrating knowledge sharing into the organizational fabric [117,118]. This suggests that knowledge sharing emerges as a trust-based exchange response driven by relational leadership dynamics.

Furthermore, the results indicated a significant and positive impact of entrepreneurial leadership on knowledge sharing. As highlighted by Adegbola et al. [119] and Chaudhuri et al. [120], entrepreneurial leaders invest in knowledge management systems and collaborative platforms to streamline information exchange, thereby improving organizational efficiency. Riana et al. [121] and Ajayi and Udeh [94] pointed out that entrepreneurial leaders foster a flexible and adaptive environment where knowledge is constantly refreshed and exchanged. This adaptability promotes a culture where employees readily share current information and insights, enhancing organizational agility and responsiveness. This indicates that knowledge sharing in this context is shaped by strategic exchange considerations, where knowledge is treated as a valuable resource aligned with opportunity-seeking behavior.

In addition, the results indicated that participative leadership has a substantial and beneficial impact on knowledge sharing. According to Kumar et al. [122] and Sarioguz and Miser [85], participative leadership actively solicits input from a diverse range of employees, enriching decision-making and problem-solving with varied insights and expertise. Additionally, Sarioguz and Miser [85] and Mata et al. [5] highlighted its promotion of cross-functional teams to tackle intricate challenges, fostering the exchange of knowledge and collaboration across different departments. This approach harnesses diverse expertise to generate more comprehensive and innovative solutions, thereby enhancing organizational outcomes. This reflects that knowledge sharing is reinforced through social obligation, where employees reciprocate participation through active knowledge contribution.

Based on the findings, empowering leadership has a significant and positive impact on knowledge sharing. Al-Romeedy [26] observed that empowering leadership delegates authority and responsibility to employees, motivating them to take ownership of their responsibilities and decisions. This delegation cultivates knowledge sharing and collaboration, fostering a sense of accountability among employees for their work. Singh [123] and Cho et al. [124] further illustrated that empowering leaders demonstrate adaptability and responsiveness to change, encouraging ongoing and pertinent knowledge sharing to address evolving circumstances. This adaptability supports organizational agility, enabling swift responses to emerging challenges and opportunities. This indicates that knowledge sharing becomes a self-initiated exchange behavior driven by autonomy and psychological ownership.

Importantly, the findings illustrated that knowledge sharing has a significant and positive impact on innovative performance. Chin et al. [125] and Devi [68] supported this conclusion, noting that knowledge sharing promotes collaboration and synergy among employees, leveraging their combined strengths and expertise to foster innovation. This collaborative environment harnesses the organization’s collective potential. Deng et al. [126] and Santhose and Lawrence [127] emphasized that the rapid dissemination of information facilitated by knowledge sharing accelerates the innovation process, enabling quicker, well-informed decision-making. In dynamic markets, this accelerated pace offers a notable competitive advantage by reducing the time required to develop and implement new ideas. This suggests that innovation emerges as a cumulative outcome of continuous knowledge exchange processes rather than isolated individual efforts. However, it is important to note that knowledge sharing alone does not guarantee innovation unless it is supported by organizational conditions that enable the transformation of knowledge into actionable outcomes. This finding highlights a critical limitation in prior studies that tend to overemphasize knowledge exchange without adequately considering its conversion into organizational capabilities.

The findings underscored the significant and positive impact of transformational leadership on organizational agility. According to Nuraini [128] and Dimple [129], transformational leadership emphasizes continuous learning and development, equipping employees with adaptive skills and knowledge. This focus ensures that the organization can swiftly acquire new competencies, adjust strategies, and leverage emerging trends, thereby enhancing overall agility. Additionally, Chauhan and Thangavelu [130] and Pawar and Dhumal [131] highlighted that transformational leadership enhances decision-making processes by fostering collaboration, transparency, and information sharing. By decentralizing decision-making and encouraging diverse input, transformational leaders facilitate prompt, well-informed decisions that effectively seize opportunities or manage risks. This indicates that organizational agility reflects an adaptive response to leadership-driven exchange relationships.

Also, the findings revealed that entrepreneurial leadership significantly and positively influences organizational agility. According to Yang and Bentein [132] and D’Souza [133], entrepreneurial leadership cultivates a robust entrepreneurial mindset among employees through autonomy, resources, and support, enhancing the organization’s capacity to recognize and capitalize on market shifts, thereby bolstering agility. Additionally, Khairy et al. [25] noted that entrepreneurial leaders foster a collaborative, knowledge-sharing culture by dismantling silos and promoting cross-functional collaboration. This rapid exchange of information and ideas facilitates organizational learning and enables swift adaptation to evolving customer preferences, technological advancements, and competitive landscapes. This indicates that agility reflects an adaptive response to leadership-driven exchange relationships.

Furthermore, the findings highlighted that participative leadership significantly and positively impacts organizational agility. According to Elsetouhi et al. [28], participative leadership enhances decision-making flexibility through collaborative processes, incorporating diverse perspectives, and swiftly adapting strategies to capitalize on opportunities. Sharief [134] and Mata et al. [5] emphasized that participative leadership cultivates resilience by proactively managing risks and preparing for unforeseen challenges, promoting a culture of flexibility and adaptability. This approach equips organizations to navigate complexities effectively and thrive in competitive environments. This reflects that agility is strengthened through collective exchange and shared responsibility.

The findings also revealed that empowering leadership has a significant and positive impact on organizational agility. Hermawan et al. [29] and Amoroso et al. [135] demonstrated that empowering leadership enhances organizational agility by fostering autonomy, trust, and continuous improvement. This leadership style empowers employees at all levels, making organizations more responsive, innovative, and adaptable. Pahi et al. [136] and Al-Romeedy [26] further noted that empowering leaders promote proactive problem-solving, quick issue resolution, and swift adaptation to market changes by delegating authority and valuing employee decision-making. This approach enables organizations to anticipate and respond to changes quickly, maintaining agility and a competitive edge. This reflects that agility is strengthened through collective exchange and shared responsibility.

Meanwhile, the findings indicated that organizational agility positively influences innovative performance. According to Holbeche [89], agile organizations possess the capability to swiftly redirect financial and human resources to support emerging open innovation initiatives, ensuring timely and effective implementation. This adaptability not only mitigates risks but also enhances the probability of successful outcomes. Ajayi and Udeh [94], Ciampi et al. [137], and Mao et al. [138] also emphasized that agile organizations cultivate a culture of continuous organizational learning, which is crucial for open innovation. These organizations excel in assimilating external knowledge swiftly and efficiently transferring internal knowledge to external partners, thereby bolstering their overall innovation capabilities through a seamless exchange of insights. This indicates that agility emerges from decentralized and autonomy-driven exchange processes. This suggests that organizational agility plays a pivotal role in bridging the gap between knowledge availability and innovation realization, addressing a key limitation in prior research that often treats these constructs independently rather than as interdependent mechanisms.

The mediation results provide deeper insight into how leadership influences innovative performance. This suggests that organizational agility plays a pivotal role in bridging the gap between knowledge availability and innovation realization, addressing a key limitation in prior research that often treats these constructs independently rather than as interdependent mechanisms. Specifically, knowledge sharing and organizational agility operate as complementary rather than redundant mediating mechanisms. Knowledge sharing reflects a relational exchange pathway through which employees contribute, integrate, and recombine knowledge in response to leadership behaviors. In contrast, organizational agility represents an adaptive capability that enables the organization to transform this shared knowledge into actionable and innovative outcomes. This distinction highlights that while knowledge sharing supports idea generation, organizational agility enables effective implementation. Accordingly, the findings extend prior research by demonstrating that innovation emerges through a multi-layered process involving both relational and adaptive mechanisms, rather than direct leadership effects alone. The mediation results go beyond merely confirming indirect effects and instead provide a more nuanced understanding of the mechanisms through which leadership influences innovation.

It is also noteworthy that the relatively similar magnitudes of the path coefficients across the four leadership styles may reflect the integrated nature of leadership practices within organizational settings. Rather than functioning in isolation, these leadership styles tend to co-occur and reinforce one another, shaping a holistic leadership environment that supports innovation. This pattern suggests that innovative performance is not driven by a single dominant leadership style, but rather emerges from the combined influence of multiple leadership behaviors. From a SET perspective, this indicates that different exchange mechanisms may operate simultaneously, collectively enhancing employees’ adaptive and innovative responses. Accordingly, the findings highlight the importance of viewing leadership as a multidimensional and synergistic construct rather than a set of independent or competing styles. This finding challenges the traditional linear perspective of leadership–innovation relationships and instead supports a more complex, process-based view in which multiple mediating mechanisms operate simultaneously.

Taken together, these findings move beyond descriptive confirmation and offer a theoretically grounded explanation of how leadership operates as a multidimensional and interaction-based phenomenon. The study, therefore, contributes to the literature not by reiterating known relationships but by demonstrating that innovation emerges from the interplay of multiple leadership styles operating through integrated social exchange mechanisms, particularly within complex and dynamic service contexts such as tourism and hospitality.

5.2. Theoretical Implications

The present study offers several important theoretical contributions by extending and refining SET within the context of tourism and hospitality organizations. Specifically, the study advances SET by demonstrating that exchange relationships are not uniform but multi-layered and differentiated processes activated by distinct leadership styles. The findings show that transformational, entrepreneurial, participative, and empowering leadership behaviors generate different forms of exchange relationships—ranging from trust-based reciprocity and obligation-driven exchanges to autonomy-oriented and value-based interactions. This moves SET beyond its traditional monolithic interpretation and positions it as a more dynamic and context-sensitive theoretical framework.

Second, the study reconceptualizes knowledge sharing as an exchange-based relational mechanism rather than a simple behavioral outcome. Drawing on the empirical findings, knowledge sharing is framed as a reciprocal response embedded in trust, perceived support, and mutual benefit. This perspective extends prior research by demonstrating that knowledge sharing operates as an intermediate social exchange process through which leadership effects are transmitted, rather than merely being a direct outcome of leadership influence.

Third, the study extends SET by introducing organizational agility as a higher-order adaptive outcome of exchange processes, thereby linking micro-level interactions to macro-level organizational capabilities. The results suggest that leadership-driven exchanges at the individual level (e.g., trust, participation, and empowerment) accumulate and transform into collective adaptive capabilities, offering a novel explanation of how exchange dynamics scale from individuals to organizations.

Fourth, the study makes a significant contribution by proposing a dual mediation (parallel) model, demonstrating that innovative performance emerges through two complementary mechanisms: a relational pathway (knowledge sharing) and an adaptive pathway (organizational agility). This finding advances the existing literature by moving beyond single-mediator models and providing a more comprehensive explanation of how leadership effects unfold across multiple levels of analysis.

Finally, the study contributes to leadership theory by advancing a configurational perspective of leadership within SET, where multiple leadership styles operate simultaneously rather than independently. The findings suggest that leadership behaviors interact and reinforce one another, creating complex exchange environments that shape employee responses and organizational outcomes. This challenges the dominant assumption of isolated leadership effects and offers a more realistic and theoretically grounded understanding of leadership dynamics, particularly in service-intensive and interaction-driven contexts such as tourism and hospitality.

5.3. Practical Implications

This study provides a set of actionable implications for tourism and hospitality organizations seeking to enhance innovative performance through leadership development, knowledge sharing, and organizational agility. While prior research has emphasized the importance of these factors, the present study translates these relationships into more operational and context-sensitive recommendations.

First, the findings suggest that organizations should prioritize the development of empowering and transformational leadership styles, as they demonstrated relatively stronger direct and indirect effects on innovative performance. Empowering leadership enhances employees’ autonomy, engagement, and willingness to participate in knowledge-sharing processes, while transformational leadership plays a central role in shaping a shared vision, motivating employees, and fostering a collaborative organizational climate. In contrast, participative and entrepreneurial leadership styles remain important but are more context-dependent, being particularly effective in situations requiring collective decision-making or opportunity exploration. Accordingly, managers should adopt a contingency-based leadership approach, selecting and combining leadership styles based on organizational needs rather than relying on a single dominant style.

Second, to operationalize leadership development, organizations are encouraged to adopt a structured leadership development toolkit that links each leadership style to observable behavioral indicators, targeted training interventions, and performance evaluation mechanisms. For example, transformational leadership can be developed through visioning workshops, inspirational communication training, and change management programs. Empowering leadership can be strengthened through delegation practices, autonomy-supportive management training, and employee involvement initiatives. Participative leadership may be enhanced through collaborative decision-making frameworks and team facilitation training, while entrepreneurial leadership can be fostered through innovation labs, opportunity recognition training, and risk-taking simulations. The effectiveness of these interventions should be evaluated using multi-source feedback mechanisms (e.g., 360-degree assessments), innovation-related KPIs, and employee engagement indicators.

To further support implementation,

Table 8. Leadership Development Toolkit.

Leadership Style	Behavioral Indicators	Training Modules	Evaluation Methods	Implementation Priority
Transformational Leadership (TRL)	Articulates vision, inspires employees, and encourages change	Visioning workshops, strategic communication, and change management training	360-degree feedback, employee motivation scores, innovation climate surveys	High (foundation for culture & direction)
Empowering Leadership (EML)	Delegates authority, promotes autonomy, supports initiative	Delegation training, empowerment coaching, autonomy-support programs	Employee engagement, participation in knowledge sharing, and innovation involvement	Very High (direct impact on innovation)
Participative Leadership (PRL)	Involves employees in decisions, promotes collaboration	Team facilitation, collaborative decision-making workshops	Decision quality, team satisfaction, and knowledge exchange frequency	Medium (context-dependent)
Entrepreneurial Leadership (ENL)	Encourages risk-taking, identifies opportunities, supports innovation	Innovation labs, opportunity recognition training, and risk management simulations	Number of new ideas, innovation outputs, and new market initiatives	High in dynamic environments

presents a leadership development toolkit that integrates behavioral indicators, training modules, evaluation methods, and implementation priorities for each leadership style.

In line with these priorities, organizations should allocate greater resources and investment toward empowering and transformational leadership development initiatives, given their stronger impact on innovation outcomes, while selectively investing in participative and entrepreneurial leadership based on contextual needs and strategic objectives.

Third, the results highlight the importance of a context–leadership style matching approach, where leadership priorities vary according to organizational conditions. For instance, start-up and high-growth organizations operating in dynamic environments benefit more from entrepreneurial and empowering leadership styles, which facilitate rapid adaptation, experimentation, and opportunity recognition. In contrast, mature organizations in relatively stable environments are more likely to benefit from transformational and participative leadership styles that support knowledge integration, alignment, and incremental innovation. Similarly, small and medium-sized enterprises (SMEs) may require flexible and entrepreneurial leadership approaches, whereas large organizations may benefit more from structured participative and transformational leadership systems. In decline or crisis contexts, organizations may rely more heavily on transformational and empowering leadership styles to support organizational renewal, restructuring, and recovery.

To guide managerial decision-making,

Table 9. Context–Leadership Style Matching Matrix.

Organizational Context	Recommended Leadership Styles	Rationale
Start-up/Growth (Dynamic Market)	ENL + EML	Supports rapid adaptation, innovation, and opportunity exploitation
Mature Organization (Stable Market)	TRL + PRL	Enhances alignment, knowledge integration, and incremental innovation
SMEs	ENL + EML	Requires flexibility, speed, and entrepreneurial thinking
Large Enterprises	TRL + PRL	Supports coordination, structure, and large-scale knowledge sharing
Decline/Crisis Context	TRL + EML	Supports organizational renewal, restructuring, and recovery

presents a simplified context–leadership style matching matrix.

Fourth, this study proposes a synergistic cultivation pathway between knowledge sharing and organizational agility, emphasizing that these mechanisms should be developed in an integrated manner rather than independently. At the organizational design level, firms should establish flexible structures, cross-functional teams, and decentralized decision-making processes to facilitate knowledge flows and responsiveness. At the human resource level, organizations should embed knowledge-sharing behaviors into performance appraisal systems, training programs, and reward mechanisms, while also promoting learning-oriented cultures that support experimentation and continuous improvement. At the technological level, implementing digital knowledge management systems, collaborative platforms, and AI-supported analytics can enhance both knowledge accessibility and organizational responsiveness. This integrated approach ensures that knowledge is not only created and shared but also effectively translated into adaptive actions and innovation outcomes.

Finally, organizations are encouraged to develop a leadership diagnostic tool based on the findings of this study to assess the presence and effectiveness of different leadership styles within the organization. Such a tool may take the form of a structured questionnaire or a 360-degree assessment instrument that evaluates leadership behaviors related to vision, empowerment, participation, and innovation support. The results of this assessment can guide targeted leadership development initiatives and help organizations align leadership capabilities with strategic innovation objectives.

5.4. Limitations and Future Research

The study acknowledges several limitations, each of which presents opportunities for future research to enhance understanding and validate findings. Given the cross-sectional nature of the data, the study is limited in its ability to establish causal relationships among the examined variables. Conducted within a specific cultural context (Egypt), the study’s findings were not readily applicable to other regions or cultural settings. Future research could replicate the study in diverse cultural contexts such as Saudi Arabia, the UAE, or Turkey to explore and contrast the outcomes. This involves conducting similar studies across different countries and regions to ascertain whether the relationships between leadership styles, knowledge sharing, organizational agility, and innovative performance remain consistent across varied cultural contexts. Further, the use of convenience sampling may limit the generalizability of the findings beyond the studied sample. Although efforts were made to include a large and diverse group of respondents, the non-probability sampling approach may introduce selection bias. Future research is encouraged to employ probability sampling techniques to enhance external validity.

In addition, although procedural and statistical remedies were applied to reduce common method variance (CMV), including Harman’s single-factor test and full collinearity assessment, it is acknowledged that these techniques may not completely eliminate common method bias. Future research is encouraged to apply more advanced approaches, such as marker variable techniques or unmeasured latent method factor methods, to further validate the robustness of the findings.

Likewise, the study concentrates on two specific sectors within the tourism and hospitality industry (travel agencies and five-star hotels), potentially restricting the generalizability of its findings to other sectors. Future research could investigate how knowledge sharing and organizational agility mediate the relationship between leadership styles and innovative performance across various sectors. Comparative studies spanning different sectors, like airlines and destination management companies, would enable the identification of industry-specific dynamics and assess the broader applicability of the study’s conclusions.

The study analyzed each leadership style individually without exploring potential interactions or combinations that could influence knowledge sharing and organizational agility. Future research could delve into these interactions and combinations of different leadership styles. Investigating how these leadership styles, along with others like transactional, charismatic, authentic, strategic, and digital, complement or oppose each other could offer insights into the most effective leadership strategies. In addition, while the study examined how knowledge sharing and organizational agility mediate the effects, it may not fully encompass all possible mediating mechanisms or conditions. Future research could explore more deeply the specific pathways through which leadership styles affect these mediating variables and, consequently, influence innovative performance. For instance, investigating how leadership behaviors cultivate organizational cultures of learning, experimentation, and adaptability could offer insights into the fundamental processes driving innovation outcomes.

Moreover, the study did not extensively investigate potential moderating factors that could impact the relationships between leadership styles, knowledge sharing, organizational agility, and innovative performance. Future research is encouraged to incorporate moderating variables such as perceived organizational support, task complexity, and organizational culture (e.g., collectivism vs. individualism) to examine the boundary conditions under which leadership styles exert their influence through mediating mechanisms. Such an approach would enable a deeper understanding of when and for whom these relationships are strengthened or weakened.

In addition, control variables such as organizational size, employee tenure, and enterprise type (e.g., travel agencies vs. five-star hotels) were not explicitly incorporated into the structural model. Future research should include such variables to test the robustness of the main effects and provide more precise estimates of the relationships under investigation.

Lastly, although the study collected data from a large number of organizations, the analysis was conducted at the individual level without explicitly accounting for potential organizational clustering (nesting effects). This may influence the independence of observations. Future research is encouraged to adopt multi-level analytical approaches to better capture both individual- and organizational-level effects. Furthermore, although the present study adopts a parallel mediation structure, alternative model specifications were not empirically compared. Future research is encouraged to test competing models, such as full mediation, partial mediation, and sequential (chain) mediation models, and to compare their explanatory power using model fit indices (e.g., AIC, BIC), thereby providing stronger validation of the proposed theoretical structure. In addition, longitudinal research designs are recommended to better capture the temporal dynamics of these relationships and to verify the causal ordering between leadership behaviors, mediating processes, and innovation outcomes over time. Also, future research may examine whether the relative strength of knowledge sharing versus organizational agility as mediators varies across different service contexts, particularly in high-contact versus low-contact environments.