Exploring R&D network resilience under risk propagation: An organizational learning perspective

Hui Liu, Bingbing Su, Min Guo and Jingbei Wang

International Journal of Production Economics, 2024, vol. 273, issue C

Abstract: Through the development of a risk propagation model, this paper investigates R&D network resilience under risk propagation from an organizational learning perspective. Drawing from organizational learning theory, we first quantify failure experience in the context of risk propagation. Then a risk propagation model is developed, which is composed of two parts: spontaneous mechanism and propagation mechanism. Finally, we implement agent-based simulation to show how organizational learning and forgetting impact on R&D network resilience and firm vulnerability under risk propagation. Our results show a significant association between organizational learning and both network resilience and firm vulnerability. However, the results differ in different levels of risk. When the propagation probability is low, network resilience can be enhanced through improving the learning ability or decreasing forgetting for both high-vulnerable and low-vulnerable firms. However, in other scenarios, the low-vulnerable firms are more critical to network resilience. Additionally, the impact of firm failure magnitude on enhancing network resilience will gradually decrease with the increase of firm learning rate. Our results will help practitioners understand the effect of organizational learning on R&D network resilience and support decision-making in risk management.

Keywords: Network resilience; Risk propagation; Organizational learning (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527324001233
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:273:y:2024:i:c:s0925527324001233

DOI: 10.1016/j.ijpe.2024.109266

Access Statistics for this article

International Journal of Production Economics is currently edited by Stefan Minner

More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().