## 2 Theoretical Framework  
[PERSON]'s foundational work positioned technological advancements as catalysts of competitive advantage and economic growth, paving the path for innovation theory [15]. This aligns with open innovation principles emphasizing leveraging diverse knowledge sources for optimal outcomes [16]. Over time, innovation theories have evolved to address innovation processes' dynamic, nonlinear, and interdependent nature. Public administration and management have gained prominence in innovation research, with scholarsemphasizing the magnitude of the complexity of management in Public Sector Innovation (PSI) [17, 18]. Thus, the complexity theory frames innovation as an emergent property of interconnected systems shaped by organizational structure, culture, and external factors [19, 20].  
Knowledge management is pivotal to generating innovation, with the concept of knowledge as \"justified true belief\" serving as the foundation for an organization's ability to create and implement new ideas. This definition highlights the importance of reliable and well-supported information that can effectively inform decision-making and drive innovation. In an organizational context, it highlights the importance of ensuring that knowledge-driven innovation and strategic decisions are both credible and actionable. Complexity theory further reinforces this by emphasizing the need for dynamic knowledge flows, as rigid structures and siloed thinking impede adaptability in complex systems. Effective knowledge management involves systematic processes for acquiring, interpreting, and utilizing knowledge, which not only foster innovation but also serve as a core strategic resource for driving creativity and achieving a competitive advantage [21]. Within this context, the Knowledge-Based View (KBV), along with the Resource-Based View (RBV), frames knowledge as \"Valuable, Inimitable, Rare, and supported by Organizational Capabilities (VIRO)\" [22, 23, 24, 25]. Complexity theory also reinforces these ideas, emphasizing the interdependencies and emergent behaviors within dynamic environments.  
Challenges such as resistance to change, motivational deficits, and insufficient training often hinder innovation within the public sector. Addressing these challenges necessitates a complexity-informed approach that balances structured processes with adaptability [21]. Key practices include fostering open communication, reducing knowledge hiding, and establishing feedback loops, which are essential to address challenges dynamically. Employees feel empowered when they have access to resources and opportunities for continuous learning that enhance engagement, creativity, and adaptability, which are crucial for managing complex innovation systems [26].  
Open innovation complements these strategies by integrating internal and external knowledge sources [16] and addressing challenges like siloed thinking and resistance to change. Complexity theory supports open innovation's iterative processes and diverse perspectives, enabling organizations to adapt to changing environments [27]. The framework proposed by [PERSON] et al. [28] combines open innovation with business process management, emphasizing value co-creation and aligning strategic and operational priorities. Complexity theory enhances this framework by stressing the role of adaptive processes, dynamic networks, and feedback mechanisms.  
Integrating RBV, KBV, open innovation, and complexity theory provides a comprehensive and robust framework for navigating PSI challenges to achieve resilience and competitive advantages in increasingly complex, dynamic ecosystems, ensuring their processes remain effective and responsive to change.