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The complexity of innovation strategy: an agent-based approach
 

The complexity of innovation strategy: an agent-based approach

Linda Ponta, Raffaella Manzini Silvano Cincotti
Advances in social simulation: proceedings of the 20th social simulation conference, Delft, The Netherlands, 25-29 August, 2025, pp.487-499
Springer proceedings in complexity
20th Annual Social Simulation Conference, SSC 2025, 357959 (Delft, The Netherlands, 25/08/2025–29/08/2025)
30/07/2026
: 2-s2.0-105046989835
: https://doi.org/10.1007/978-3-032-31712-4_36
: WOS:001851564000036
Agent-based modeling Firm performance Innovation License Patent
Innovation strategy is one of the most critical decisions firms face. Beyond the traditional make-or-buy dichotomy, hybrid and plural sourcing approaches, such as strategic alliances, highlight a third strategic option: collaboration. This study examines the combined effects of “making” (independently or jointly with partners) and “buying” innovation on firm performance. We develop an agent-based model and simulator in which heterogeneous firms are embedded in a directed random graph, enabling the analysis of interaction-driven innovation dynamics. Results indicate that the most advantageous strategy for economic performance varies with sectoral innovation intensity, underscoring the contextual nature of innovation choices. The agent-based approach reveals complex emergent behaviors and provides insights into how strategic decisions propagate through the system. These findings emphasize the importance for managers and policy-makers of adopting a holistic view of the innovation process and considering the interplay between internal development, external sourcing, and collaborative activities.
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