Reacting and recovering after an innovation failure. An agent-based approach

Linda Ponta, Gloria Puliga, Raffaella Manzini and Silvano Cincotti

Technovation, 2024, vol. 129, issue C

Abstract: A company's growth depends not only on its achievements but also on how it can recover from failures. The study of innovation failure and learning-from-failure has gained attention over the years. Described as a complex problem, the dynamic of learning occurs as a non-linear phenomenon. Therefore, this study develops an agent-based model to examine and investigate, as a complex system, the impact on firms' performance of two main possible strategies of learning-from-failure, i.e. (1) the leveraging of the own experience and (2) the use of external resources. The findings suggest that embracing a learning-from-failure strategy in the innovation process enhances the firms' performance. In addition, the innovation intensity of the sector influences the impact of the strategy chosen. Comparing the use of internal vs external resources, the former seems to be a better strategy for enhancing the company's performance.

Keywords: Failure; Patents; Open innovation; Agent-based models (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:129:y:2024:i:c:s0166497223001955

DOI: 10.1016/j.technovation.2023.102884

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