Systemic Risks in Society and Economics

Helbing, Dirk

doi:10.1007/978-3-642-24004-1_14

Cited by 44 publications

(20 citation statements)

References 82 publications

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“…Helbing [12] expressed that the catastrophe engendered by human factors can not be clarified by analytical approaches only but rather requires a collective comprehension of the social dynamics.…”

Section: Literature Reviewmentioning

confidence: 99%

Connectivity, Information Jumps, and Market Stability: An Agent-Based Approach

Khashanah

Alsulaiman

2017

Complexity

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We propose a metamodel to assess simulated market stability by introducing information connectivity in an agent-based network. The market is occupied by heterogeneous agents with different behaviors, strategies, and information connectivity. A jump-diffusion process simulating events that may occur in the market is introduced. Agents information awareness varies along with agents propensity to respond to the information jump and jump size. A jump reshuffles market positions based on agents risk preferences determined by behavior and strategy. We examine the effect of information awareness on the volatility index of the simulated market in a scale-free market network. The analysis is performed by developing five experiments wherein the first one corresponds to systemic information ignorance state. Three experiments examine the role of hubs, normal agents, and hermits in the network when intermediate combinations of agent types have information awareness. The fifth experiment corresponds to the systemic information awareness with all agents being informed. The results show that the simulated market is driven to instability in a similar manner to patterns observed in a crisis where all agents become homogeneous in information awareness of events. Hubs contribute to increased connectivity and act as amplifiers of good, bad, or inaccurate information or sentiment.

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Section: Literature Reviewmentioning

confidence: 99%

Connectivity, Information Jumps, and Market Stability: An Agent-Based Approach

Khashanah

Alsulaiman

2017

Complexity

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“…Examples include disease epidemics, traffic congestion, and electrical power system blackouts. These phenomena are known as cascade failures, chain reactions, avalanches or domino effects [1]. The most common feature of cascade failures is that a local failure event results in a global failure on a larger scale.…”

Section: Introductionmentioning

confidence: 99%

Synchronized control of socio-economics systems and wisdom of collective

Namatame

2013

2013 3rd International Conference on Instrumentation Control and Automation (ICA)

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The increasing scale and complexity of networked systems has necessitated a new control approach. Since the network topology has a direct impact on performance such as resilience and robustness, a mechanism of self-control is an important and immediate requirement. The network topology is the most fundamental network property on which self-control is deployed, and the control over the topology has a direct impact on system performances. The wisdom of crowds refers to the phenomenon in which the collective knowledge of a community is greater than the knowledge of any individual. Consensus and synchronization problems are closely related to the variety of issues such as collective behavior in nature, the interaction among agents as a matter of the robot control, and building efficient wireless sensor networks. In this paper I propose a synchronized control of networked systems that build on concepts of graph theory. The synchronized control of networked systems is performed in a decentralized manner where the selfcontrol is employed at each node. Using prototype simulations, it is demonstrated that which nodes should be put on high priority so that the network performance is mostly improved.

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“…Work around the dynamical processes that can undermine (or enhance) the operation of such systems has become increasingly relevant (Vespignani, 2012), with the case of failure cascades being at the forefront due to its evident practical implications (the economic crisis of 2007-2008 being a recent hallmark of its importance (Helbing, 2012)). …”

Section: Introductionmentioning

confidence: 99%

“…Hence studies on systemic risk typically focus on (a) i.e. the probability of systemic risk to materialise (Helbing, 2012; 4 A system is a general class of objects, which exists "in a given environment, aims at reaching some objectives (teleological aspect) by doing an activity (functional aspect) while its internal structure (ontological aspect) evolves through time (genetic aspect) without losing its own identity. Projects can thus be considered as systems."…”

Section: Introductionmentioning

confidence: 99%

Project systemic risk: Application examples of a network model

Ellinas¹,

Allan

Johansson³

2016

International Journal of Production Economics

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. are identified. In the case of the latter (conflict), the effect of (sub) contractor activity -in terms of variance and activity pattern -to project systemic risk is assessed. To do so, numerical methods are developed and applied on an empirical dataset of widely-captured data (Gantt charts). In the context of the two challenges proposed, it is shown that: (a) the exposure of a project to systemic risk varies in a non-trivial manner as it evolves, at both micro and macro level; (b) (sub) contractor activity substantially impacts the emergence of locally important tasks (i.e. tasks able to disrupt the operation of a (sub) contractor). From a theoretical perspective, this work initiates a dialogue between the two domains (PM and NS), potentially opening new ways of tackling long-lasting challenges of PM.

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Systemic Risks in Society and Economics

Cited by 44 publications

References 82 publications

Connectivity, Information Jumps, and Market Stability: An Agent-Based Approach

Connectivity, Information Jumps, and Market Stability: An Agent-Based Approach

Synchronized control of socio-economics systems and wisdom of collective

Project systemic risk: Application examples of a network model

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