Modelling indirect interactions during failure spreading in a project activity network
Christos Ellinas

TL;DR
This paper introduces a model that incorporates both direct and indirect (subsequent) exposures to better understand failure spreading in project networks, revealing significant impacts on spread size, rate, and structure.
Contribution
It presents a novel model that explicitly accounts for indirect interactions in failure propagation, enhancing understanding of spreading dynamics in engineering projects.
Findings
Subsequent exposure significantly affects spreading size and rate.
Hidden influential nodes emerge during large-scale spreading.
Direct and indirect exposures jointly influence failure dynamics.
Abstract
Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect interactions remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and subsequent exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that subsequent exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation…
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