Our Research
Our team's published research papers forming the foundation of our technology.
Dr. Christos ellinas, Christo Nicolaides, Demetris Avraam
Published in Journal of Physics: Complexity
Neglecting complex network structures underestimates delays in a large-capital project
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The study looks at completing big projects on time, specifically focusing on how delays in one activity affect others. Contrary to current theories, the research suggests that these delays are underestimated because they ignore certain structural features in the project's network. The study proposes a new approach that considers both timing and structure to better predict and understand how delays spread in projects.
Dr. Alexei Vazquez, Iacopo Pozzana, Dr. Georgios Kalogridis & Dr. Christos Ellinas
Published in nature scientific reports
Activity networks determine project performance
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Projects have a critical path, a sequence of activities crucial for on-time project completion. Project managers often focus intensely on this path, overlooking the broader network structure's impact on it. Using a generative model and data from 77 projects (totalling over $10 billion), the study reveals that the network structure extends beyond the critical path.
The proposed duplication-split model predicts consistent patterns in real projects, emphasising that delay propagation in project schedules is a network property, not limited to the critical path.
dr. Christos Ellinas, dr. Christos Nicolaides, dr. Naoki Masuda
Published in Journal of Computational Social Science
Mitigation strategies against cascading failures within a project activity network
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Ensuring timely project delivery is crucial for addressing societal challenges, yet projects are challenging due to their complex and interconnected nature, making them prone to cascading failures. The study develops a cascading failure model and tests it on a temporal activity network from a large engineering project.
Evaluating six mitigation strategies, the research surprisingly finds that, in most cases, the temporal properties of activities are more crucial than their structural properties in preventing large-scale cascading failures. These findings suggest new approaches for designing and scheduling projects to naturally limit the impact of cascading failures.
dr. Christos Ellinas, dr. Marc Santolini, dr. Christos Nicolaides
Published At EPD Data Science
Uncovering the fragility of large-scale engineering projects
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Engineering projects often face challenges in timely completion, with delays spreading across interconnected activities. Using data from 14 diverse large-scale projects, the study uncovers perturbation cascades, where delays in one activity impact up to 4 downstream activities, causing significant overall project delays.
Perturbation clustering is identified as a crucial factor, with poorly performing projects experiencing major disruptions in high-reach nodes, leading to large cascades. In contrast, well-performing projects have perturbations in low-reach nodes, resulting in localized cascades. The findings suggest a network-science framework for improving the delivery of large-scale engineering projects.
dr. Christos Ellinas, dr. Georgios Kalogridis & dr. Konstantinos Sakellariou, IACOPO POZZANA
Published in Applied Network Science
Spreading of performance fluctuations on real-world project networks
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Understanding the impact of individual nodes is crucial in studying spreading processes on networks. The study introduces a novel metric, reachability-heterogeneity (RH), to quantify each node's contribution to network robustness against spreading processes. Using data from four large engineering projects, the study validates the RH metric, finding that nodes with low RH consistently perform better.
The comparison with seven other node metrics reveals the interdependence of RH with activity performance. The context-agnostic nature of RH, demonstrated with real-world data, emphasises the role of network structure in overall project performance.
dr. Christos Ellinas
Published in Production and Operations Management
The Domino Effect: An Empirical Exposition of Systemic Risk Across Project Networks
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Activity network analysis is commonly used for project risk management, assuming linear cause-and-effect relationships. This study challenges this assumption, using a computational framework on real-world project data to assess project systemic risk.
It finds that local failures can trigger cascading effects, with even small disruptions causing large systemic failures more frequently than anticipated.
The study attributes these failures to the topological and temporal features of activity networks, highlighting the inadequacy of local mitigation efforts. The findings contribute to a better understanding of the causal mechanisms behind large-scale project failures.
DR. Alexei Vazquez, DR. Chrysostomos Marasinou, DR. Georgios Kalogridis, DR. Christos Ellinas
Published in Physica A: Statistical Mechanics and its Applications
Activity delay patterns in project networks
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Delays in activities completion drive human projects to schedule and cost overruns. It is believed activity delays are the consequence of multiple idiosyncrasies without specific patterns or rules. Here we show that is not the case. Using data for 180 construction project schedules, we demonstrate that activity delays satisfy a universal model that we call the law of activity delays. After we correct for delay risk factors, what remains follows a log-normal distribution.
dR. Alexei Vazquez
Published in American Physical Society Phys. Rev. E
Emergence of network communities driven by local rules
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Natural systems are modeled by networks with nodes and links. Often, the nodes are segregated into communities with different connectivity patterns. Node heterogeneity such as political affiliation in social networks or biological function in gene networks is highlighted as a key factor driving the segregation of nodes into communities. Here, by means of numerical simulations, I show that node heterogeneity is not a necessary requirement. To this end I introduce the Ramsey community number 𝑟𝜅, the minimum graph size that guarentees the emergence of network communities with almost certainty. Using the stochastic block model and Infomap methods for community detection, I show that networks generated by local rules have finite 𝑟𝜅 values, while their randomized versions do not have emergent communities. I conjecture that network communities are an emergent property of networks evolving with local rules.
dR. Alexei Vazquez
Published in Journal of Complex Networks, Volume 13, Issue 1,
Percolation in higher order networks via mapping to chygraphs
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Percolation theory investigates systems of interconnected units, their resilience to damage and their propensity to propagation. For random networks, we can solve the percolation problems analytically using the generating function formalism. Yet, with the introduction of higher order networks, the generating function calculations are becoming difficult to perform and harder to validate. Here, I illustrate the mapping of percolation in higher order networks to percolation in chygraphs. Chygraphs are defined as a set of complexes where complexes are hypergraphs with vertex sets in the set of complexes. In a previous work, I reported the generating function formalism to percolation in chygraphs and obtained an analytical equation for the order parameter. Taking advantage of this result, I recapitulate analytical results for percolation problems in higher order networks and report extensions to more complex scenarios using symbolic calculations. The code for symbolic calculations can be found at github.com/av2atgh/chygraph.
dR. Alexei Vazquez
Published in The European Physical Journal B
Emerge of scaling in project schedules
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A project schedule contains a network of activities, the activity durations, the early and late finish dates for each activity, and the associated total float or slack times, the difference between the late and early dates. Here I show that the distribution of activity durations and total floats of construction project schedules exhibit a power law scaling. The power law scaling of the activity durations is explained by a historical process of specialization fragmenting old activities into new activities with shorter duration. In contrast, the power law scaling of the total floats distribution across activities is determined by the activity network. I demonstrate that the power law scaling of the activity duration distribution is essential to obtain a good estimate of the project delay distribution, while the actual total float distribution is less relevant. Finally, using extreme value theory and scaling arguments, I provide a mathematical proof for reference class forecasting for the project delay distribution.
dR. Alexei Vazquez
Published in Chaos, Solitons & Fractals
Manageable to unmanageable transition in a fractal model of project networks
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Project networks are characterized by power law degree distributions, a property that is known to promote spreading. In contrast, the longest path length of project networks scales algebraically with the network size, which improves the impact of random interventions. Using the duplication-split model of project networks, I provide convincing evidence that project networks are fractal networks.