Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/327395 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Innovation & Knowledge (JIK) [ISSN:] 2444-569X [Volume:] 9 [Issue:] 2 [Article No.:] 100490 [Year:] 2024 [Pages:] 1-13
Publisher: 
Elsevier, Amsterdam
Abstract: 
The prevalence of digital ecosystems and platforms underscores the need for a deeper understanding of the factors that influence performance variations within these platforms. This study introduced a multidimensional model to examine the platform ecosystem characteristics that affect performance outcomes. To this end, it adopted the Lotka-Volterra complex system theory. The model was simplified into a one-dimensional framework, enabling the examination and prediction of the relationship between performance bifurcation and configurations of platform characteristics. This study provides practical insights and implications that extend beyond academia. The results reveal that high network threshold values indicate robust platform performance, suggesting resilience against collapse. Additionally, increasing the network effect influences platform performance by shifting competition strength toward prominent tipping-point locations, which is considered a desirable regime. The results further confirm that competition dampens a platform's exponential growth; however, cross-network effects enhance it. These insights have significant implications for investors, offering a practical vision that can inform managers' strategic decision-making. These findings provide a solid foundation for developing informed strategies to enhance platform performance. In a world in which digital ecosystems play a pivotal role, the implications of this study empower stakeholders to make data-driven decisions, fostering success in a dynamic and competitive digital business environment.
Subjects: 
Bifurcation performance
Critical transition point
Lotka-Volterra theory
Platform ecosystem configuration
Tipping point
JEL: 
D85
C51
C45
L14
L22
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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