In an era marked by transformative challenges, such as sustainability transition and digital transformation, the need for innovative and effective solutions has never been more urgent. Successfully navigating these challenges requires organizations to adopt a complex perspective— that balances the need for immediate action with a forward-looking vision.  This Special Interest Group seeks groundbreaking research that addresses these complexities, offering new models, methods, and tools for a rapidly evolving world.
Complexity represents a mandatory approach to properly address research questions in future horizons in economic, financial, managerial, organizational and innovation systems. In fact, these systems are Complex Adaptive Systems characterized by non-linear relations among their constitutive elements, heterogeneity, self-reflexivity, emergent properties, self-organization, expectations, and dynamic continuous adaptation.
The theory of Complex Adaptive Systems (CASs) was applied in many studies. CASs are systems of multiple and interconnected agents that emerge into coherent forms without any single entity deliberately managing the entire system. Organizations, supply chains, industrial districts, industrial symbiosis networks, and Regional Innovation Systems are framed as CASs, whose dynamics and behavior follow the CAS properties such as interconnectedness, adaptation at the edge of chaos, adaptive learning, resilience, co-evolution and emergence.

Agent-Based Modelling and Simulation (ABM&S) is one of the most adopted methodologies to cope with the analysis of complex social systems, such as social groups, organizations, inter-organizational networks, innovation networks, or, in general, territorial innovation systems and macro-economic systems. In the last two decades, ABM&S has been increasingly recognized not only as a suitable research approach to build theory and advance the understanding of complex adaptive systems but also as an adequate policy advice tool, particularly regarding regional or local innovation systems of energy and digital transitions.
Complexity theory and complex adaptive systems let to gain an appropriate perspective and the use of proper methodological tools to analyze economic, innovation, management, and organizational issues.
In particular, a complexity approach, i.e. a dynamic and systemic approach, allows modeling complex system behaviors, reproducing the internal dynamics of the whole system from the bottom, focusing on its microelements such as the agents, their attributes, actions, goals, coordination mechanism and the network structure (and type of relationships) that connects them.
Moreover, by exploiting the complexity approach it is possible to consider the ecosystem in which organizations evolve. Thus, all the value and supply chains can be investigated, and all the coordination mechanisms among the different actors can be studied.
In addition, the diffusion of new technologies for massive data collection offers the opportunity to measure and evaluate complex system dynamics through data-driven methodologies. New tools can be used to collect large amounts of rich, high-quality, and reliable data, in almost real-time. They provide automatic and more objective measurements of individual, team, and firm behaviors, supporting scholars in analyzing complex systems.

As organizations and societies explore increasingly complex and uncertain conditions, embracing systemic thinking, integrating multiple perspectives, and leveraging advanced methodological approaches will be key to addressing contemporary challenges. The SIG aims to foster a deeper dialogue on these issues, encouraging research that advances theoretical, empirical, and methodological understanding of complexity in management, innovation, and organizational studies. 
For example, innovative methods and tools of text mining and social network analysis can be employed to study how knowledge flows within and outside organizations. These approaches enable a deeper understanding of information exchange, collaboration patterns, and the dissemination of ideas across different sectors

The SIG should discuss new methods, applications, or theoretical approaches. In particular, the SIG will focus on:
 

• investigate the drivers of complexity in management systems, value chains, business ecosystems, and organizational structures; 
• analyze the relationship between complexity and new technologies, fostering digital transformation, green-energy transition, and
• innovative and unconventional policies and regulation measures to support also social sustainable innovation processes; 
• explore approaches and tools adopted by companies to self-organize and adapt to the complexity of their external environment, highlighting how organizations manage the tension between stability and change over time
• study the impact of sustainability transition on innovation systems 
• study the impact of digital transformation and technology transfer on innovation systems
• study the impact of new technologies for sustainable transition
• study the typical paradoxes of complexity, such as tensions between continuity and discontinuity, tradition and innovation, short-term and long-term decision-making