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.

中文翻译：

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识别互连系统中隐藏的关键元素：一种考虑结构约束的影响动力学分析方法

系统分析领域传统上侧重于识别互连系统中的基本要素并分析它们之间的因果关系。然而，系统分析中的大多数决策方法都是片面的。它们主要依靠元素之间的相互作用来做出决策，而忽略了元素间不均匀的影响衰减和不等重要性的扩散。此外，这两个因素与系统的拓扑结构密切相关，这是以往研究中经常被忽视的方面，导致对隐藏关键要素的识别不准确和遗漏。为了应对这些挑战，本文引入了一种称为 SIDA（结构约束影响动态分析）的新方法。我们利用从结构空穴理论中得出的结构约束系数来描述非均匀衰减。此外，我们集成了影响力和距离加权 PageRank 算法来管理不等重要性扩散，同时考虑到系统内元素之间的影响力和距离。我们通过对制药行业生态系统的全面分析来验证我们提出的方法，将其性能与以前的方法进行比较，以验证其有效性和实用性。案例研究结果表明，SIDA 产生了更合理的元素分析和排序结果。