Identifying hidden critical elements in interconnected systems: An influence dynamics analysis approach considering structural constraints

The systems analysis field has traditionally focused on identifying the essential elements within an interconnected system and analyzing the cause-and-effect relationships among them. However, most decision-making methods in system analysis have been one-sided. They primarily rely on the interactions between elements to make decisions, neglecting to account for the non-uniform influence attenuation among elements and unequal importance diffusion. Furthermore, these two factors are closely tied to the topological structure of systems, which has been an often-overlooked aspect in previous research, leading to inaccurate identification and omission of hidden key elements. In response to these challenges, this paper introduces a novel method called SIDA (Structural-constrained Influence Dynamic Analysis). We utilize structural constraint coefficients derived from structural hole theory to describe the non-uniform attenuation. Furthermore, we integrate an influence and distance-weighted PageRank algorithm to manage the unequal importance diffusion taking into account both the influence and the distance between elements within systems. We validated our proposed method through a comprehensive analysis of a pharmaceutical industry ecosystem, comparing its performance with previous approaches to validate its effectiveness and practicality. The case study results demonstrate that SIDA produces more reasonable element analysis and ranking outcomes.