Abstract
As the full integration of human-cyber-physical has become mainstream, various services are interconnected to meet the ever-changing demands of users, forming service ecosystems. Service ecosystems constantly evolve driven by value and present many nonlinear responses, where inadvertent perturbations may lead to significant changes. This paper proposes a nonlinear dynamical model of value-driven service ecosystem evolution inspired by the energy flow of natural ecosystems, thereby explaining stability changes based on nonlinear features from the perspective of ecosystems. The model considers the nonlinear features, including interdependence and mutation of services and demands, and time delay due to service development. Further, we use stability and bifurcation theories to study the critical conditions under which parameter changes lead to phase transitions. In addition, numerical simulations are conducted to verify the effectiveness of the model and the correctness of the phase transition conditions. Through this method, service ecosystem managers can accurately predict the inflection point of the system from stable to unstable. Our method provides a novel way for the evaluation and governance of service ecosystems to have better universality and interpretability than current data-based mining methods and time series models based on neural networks.
This work was supported in part by the National Natural Science Foundation of China under Grants No.61832014, No.62032016 and No.62102281, the Jiangxi Provincial Natural Science Foundation under Grant No.20224BAB212015, the Foundation of Jiangxi Educational Committee under Grant No. GJJ210338. Zhiyong Feng is the corresponding author.
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Zhou, X., Xiao, J., Xue, X., Chen, S., Wu, H., Feng, Z. (2023). A Dynamical Model for the Nonlinear Features of Value-Driven Service Ecosystem Evolution. In: Monti, F., Rinderle-Ma, S., Ruiz Cortés, A., Zheng, Z., Mecella, M. (eds) Service-Oriented Computing. ICSOC 2023. Lecture Notes in Computer Science, vol 14419. Springer, Cham. https://doi.org/10.1007/978-3-031-48421-6_20
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