Can tiered open-source mandates optimize innovation? A differential game study osn platform vs. independent project dynamics in foundation software ecosystems
- 1School of Management Science, Dhonburi Rajabhat University, Dhonburi, Thailand
- 2School of Technology and Business, Hunan University of Information Technology, Changsha, China
Abstract
The governance of AI foundation software ecosystems requires balancing platform scale and independent innovation to ensure technological sovereignty. This paper examines whether tiered open-source mandates—with differentiated requirements for platforms and independents—can optimize ecosystem innovation. We develop and solve a tripartite Stackelberg differential game model incorporating differences in compliance costs, ecosystem dependence, and appropriation capabilities. Analysis shows that tiered mandates outperform uniform ones when heterogeneity exceeds threshold levels, optimally imposing stricter rules on platforms (θD∈[0.60,0.75]) and offering flexibility to independents (θI∈[0.25,0.40]). Ecosystem health improvements range from 15–40%, peaking under high compliance cost asymmetry (λD/λI>2.0). Key boundary conditions are identified, and an adaptive decision framework is proposed. This research formalizes differentiated mandates as an endogenous policy variable, quantifies dominance conditions, and provides actionable thresholds, demonstrating that calibrated differentiation based on structural heterogeneity can optimize innovation in AI infrastructure governance. Throughout this paper, “health improvement” refers specifically to the ecosystem architect’s composite health function H(KD,KI), a governance metric of scale, diversity, and balance, not a full measure of social welfare.
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BibTeX
@article{wu2026tiered,
title = {{Can tiered open-source mandates optimize innovation? A differential game study osn platform vs. independent project dynamics in foundation software ecosystems}},
author = {Bingyang Wu and Yongxi Yi},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0340713},
url = {https://doi.org/10.1371/journal.pone.0340713},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Can tiered open-source mandates optimize innovation? A differential game study osn platform vs. independent project dynamics in foundation software ecosystems
AU - Bingyang Wu
AU - Yongxi Yi
PY - 2026
DA - 2026/09/11
JO - PLOS One
DO - 10.1371/journal.pone.0340713
UR - https://doi.org/10.1371/journal.pone.0340713
AB - The governance of AI foundation software ecosystems requires balancing platform scale and independent innovation to ensure technological sovereignty. This paper examines whether tiered open-source mandates—with differentiated requirements for platforms and independents—can optimize ecosystem innovation. We develop and solve a tripartite Stackelberg differential game model incorporating differences in compliance costs, ecosystem dependence, and appropriation capabilities. Analysis shows that tiered mandates outperform uniform ones when heterogeneity exceeds threshold levels, optimally imposing stricter rules on platforms (θD∈[0.60,0.75]) and offering flexibility to independents (θI∈[0.25,0.40]). Ecosystem health improvements range from 15–40%, peaking under high compliance cost asymmetry (λD/λI>2.0). Key boundary conditions are identified, and an adaptive decision framework is proposed. This research formalizes differentiated mandates as an endogenous policy variable, quantifies dominance conditions, and provides actionable thresholds, demonstrating that calibrated differentiation based on structural heterogeneity can optimize innovation in AI infrastructure governance. Throughout this paper, “health improvement” refers specifically to the ecosystem architect’s composite health function H(KD,KI), a governance metric of scale, diversity, and balance, not a full measure of social welfare.
SN - 1932-6203
ER -