| Abstract: |
This article explores the coevolutionary dynamics of immature innovation
systems (IMIS), focusing on the role of marginalized agents often excluded
from Conventional Innovation Systems (CIS). Marginalized agents, such as
informal entrepreneurs or low-resource communities, are key actors in
addressing local challenges but are typically overlooked in mainstream
innovation processes, making it crucial to understand how they can be
integrated into broader systems. Using an Agent-Based Model (ABM) based on
Villalba (2023) and Ruiz et al. (2016), we examine how interactions between
agents with different innovation and inclusion capabilities drive system
evolution. The model integrates learning and unlearning processes, allowing
agents to adapt and build capabilities over time. Through simulations that
vary social thresholds, agent configurations, NOPI (Needs, Opportunities,
Problems and Ideas) complexity, and the presence or absence of learning, we
find that while higher social thresholds and complex NOPIs foster agent
specialization, they can limit the inclusion of marginalized agents.
Conversely, the absence of learning results in system stagnation despite
increased short-term inclusion. By adopting a system-wide perspective, this
paper contributes to the literature on innovation systems by analyzing how the
relationships between marginalized and conventional actors influence inclusion
dynamics. Our ABM captures the complex interplay of inclusion, coevolution,
and capability complementarity within IMIS, offering deeper insights into how
marginalized agents drive inclusive innovation and emphasizing the importance
of fostering both innovation and inclusion capabilities for sustainable,
equitable outcomes. |