Unlocking Complexity: Harnessing Value Entropy for Advanced Multidimensional Utility Evaluation in Service Ecosystems

Xiangning Yu, Xiao Xue, Deyu Zhou, Gang Wang, Zhiyong Feng

Abstract: The increasing prevalence of smart services in daily life drives the rapid emergence of service ecosystems across various domains such as E-commerce, cloud manufacturing, and crowdsourcing. Evaluating the utility of these ecosystems is challenging due to complex characteristics like diverse crowd intelligence, cascading service network effects, and the interplay of individual interests. To address these challenges, this study introduces an innovative utility evaluation model that integrates individual and systemic factors with multidimensional metrics, reconciling micro and macro perspectives. This model effectively addresses potential conflicts between individual and systemic benefits, supporting the continuous learning and evolution of agents within service ecosystems. It employs value entropy to precisely model and interpret complex nonlinear emergence phenomena. The model’s universal framework offers high customizability and broad applicability, facilitating specific adaptations across different service ecosystem scenarios. Additionally, a visual multi-agent system simulation tool has been developed to adjust agent attributes and cooperative topologies, allowing for the observation of system responses. Empirical validation confirms the model’s accuracy and provides a mechanistic explanation for emergence phenomena in human societies. The findings demonstrate the model’s high coordination and effectiveness in managing both linear and nonlinear characteristics, presenting a powerful and flexible tool for utility evaluation in service ecosystems..

External IDs:doi:10.1109/tsc.2025.3577481