scholarly journals Hungarian Energy Law as an Example of Using Complex System Viewpoints to Understand Risks in Public Administration Normativity

2020 ◽  
Vol 8 (2) ◽  
pp. 30-55
Author(s):  
Máté Tóth ◽  
Gyula Vastag

Complex networks and complex adaptive systems theories come from hard sciences. The question arises whether these viewpoints can add anything to the understanding of the operation and failures of continental normativity governing the public sector. In the first part, this paper intends to demonstrate for the first time via industry-specific examples that Hungarian energy law, one of the absolute extremes of the rigid continental law is per se following complex adaptive system attributes as being implemented by the public administration, thus refuting any reductionist and linear concepts of ‘classical’ continental public law routines and prejudice. This leads to such essential features of complex systems like emergence, the ‘robust yet fragile’ dilemma and the issue of systemic risk that we investigate in the second part, also covering unpublished case studies, letting us closer to identify risks within the law applied by public administration. This in our view can add a lot to the understanding and improvement of the quality of normativity in order to mitigate systemic risks within law and public administration.

ARGOMENTI ◽  
2009 ◽  
pp. 99-122
Author(s):  
Alessandro Minello

- Cluster policy today represent one of the main elements of the European agenda, both for policy makers and for practitioners. In the last decade an extensive-type cluster policy has produced a proliferation of clusters all over the Europe, but the generated quality of clusters created has not always been quite satisfactory. Following the input by the European commission, currently is underway a qualitative review of the goals and processes of European cluster policy. This paper aims at presenting such changes in the European cluster policy, beside the main lessons that can be learned. The analysis emphasizes some critical elements of the current process of "clustering" and highlights the role of the institutions, besides the market, in the planning of new clusters and the strengthening of those existing. The final message is that Europe needs a better cluster policy, rather than more clusters, according to the growing complexity and dynamism of clusters.Parole chiave: cluster, politica dei cluster, approccio triple-helix, sistemi adattivi complessi.Keywords: cluster, cluster policy, triple helix approach, complex adaptive systems.


Author(s):  
Marc Rabaey

This chapter introduces Complex Adaptive Systems Thinking (CAST) into the domain of Intellectual Capital (IC). CAST is based on the theories of Complex Adaptive System (CAS) and Systems Thinking (ST). It argues that the CAST, combined with Intelligence Base offers a potentially more holistic approach to managing the Intellectual Capital of an organization. Furthermore, the authors extend this IC management with additional dimensions proper to a social entity such as an organization. New organizational design methods are needed and the capability approach is such a method that supports IC in virtual and real organizations. The characteristics of Intellectual Capital are discussed in the iterative process of inquiry and the Cynefin Framework, guaranteeing a holistic view on the organization and its environment.


2017 ◽  
Vol 2 (1) ◽  
pp. 137-143
Author(s):  
Levente Bakos ◽  
Dănuț Dumitrașcu

Abstract Risk assessment is one the key activities of any project. The unexpected situations can have catastrophic consequences. Risk assessment tries to estimate to potential known unknowns, but there is no guarantee to foresee all circumstances around a project. In this situation the project team must be adaptive and find solutions by cooperation, creativity and abductive reasoning. In the paper we tried to analyse on what extent a project and a project team can be handled as a complex adaptive system. More precisely, how the scientific and practical achievements of the theory of complex adaptive systems (CAS) can be used in project management. More exactly, we analyse the applicability of the Holonic Multi-Agent Systems in risk management of the projects. We consider the way in which holons handle the unexpected situations can be a model in project management.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Paul Brous ◽  
Marijn Janssen ◽  
Paulien Herder

Organizations are increasingly looking to adopt the Internet of Things (IoT) to collect the data required for data-driven decision-making. IoT might yield many benefits for asset management organizations engaged in infrastructure asset management, yet not all organizations are equipped to handle this data. IoT data is collected, stored, and analyzed within data infrastructures and there are many changes over time, resulting in the evolution of the data infrastructure and the need to view data infrastructures as complex adaptive systems (CAS). Such data infrastructures represent information about physical reality, in this case about the underlying physical infrastructure. Physical infrastructures are often described and analyzed in literature as CASs, but their underlying data infrastructures are not yet systematically analyzed, whereas they can also be viewed as CAS. Current asset management data models tend to view the system from a static perspective, posing constraints on the extensibility of the system, and making it difficult to adopt new data sources such as IoT. The objective of the research is therefore to develop an extensible model of asset management data infrastructures which helps organizations implement data infrastructures which are capable of evolution and aids the successful adoption of IoT. Systematic literature review and an IoT case study in the infrastructure management domain are used as research methods. By adopting a CAS lens in the design, the resulting data infrastructure is extendable to deal with evolution of asset management data infrastructures in the face of new technologies and new requirements and to steadily exhibit new forms of emergent behavior. This paper concludes that asset management data infrastructures are inherently multilevel, consisting of subsystems, links, and nodes, all of which are interdependent in several ways.


2008 ◽  
Vol 2 ◽  
Author(s):  
Craig Newell

Educational theorists are making increasing use of the metaphors and concepts of complexity thinking in their discourses. In particular, Professors Brent Davis, Elaine Simmt, and Dennis Sumara have written extensively about using complexity thinking to shift attention from the individual student as the locus of learning (cognizing agent) to the social collective—the class—as the locus of learning. In this model, the class (students and teacher) is (potentially) a complex adaptive system. The students and teacher remain complex adaptive systems in their own right, but through dynamic local interactions there is the possibility of emergent behaviours indicative of learning that transcends that of the individuals within the class. The social collective we know as a class becomes an instance of the Aristotlean adage, “The whole is greater than the sum of its parts.” (With the coda that we cannot understand the whole by merely understanding the components.) Davis, Simmt, and Sumara have segued from complexity-informed descriptions of educational collectives to discussions about facilitating the self-organization of classes into complex adaptive systems – learning systems, in their language. In this paper, I discuss complex adaptive systems and look at how Davis, Simmt, and Sumara developed their thesis that the class collective, rather than individual student, is the appropriate level to investigate learning and teaching. We conclude by addressing some of the possibilities and challenges inherent in such a redescription of communities of learners.


2020 ◽  
Vol 29 (5) ◽  
pp. 779-792
Author(s):  
Masahiko Haraguchi

PurposeThis paper aims to examine how government continuity planning contributes to strengthening the public sector's emergency preparedness, resulting in enhanced resilience of the public sector. Government continuity plans (GCPs) are a recently focused concept in disaster preparedness, compared to business continuity plans (BCPs) in the private sector. The need for BCPs was widely recognized after the 2011 Great East Japan Earthquake (GEJE) and the 2011 Thailand Floods. However, recent disasters, such as the 2016 Kumamoto Earthquake in Japan, have revealed that local governments without effective GCPs were severely affected by disasters, preventing them from quickly responding to or recovering from disasters. When the GEJE occurred in 2011, only 11% of municipal governments in Japan had GCPs.Design/methodology/approachThe paper analyzes basic principles of government continuity planning using complex adaptive systems (CAS) theory while summarizing recent developments in theory and practice of government continuity planning.FindingsThis research investigates the Japanese experience of GCPs using self-organization, one of the concepts of CAS. A GCP will complement regional disaster plans, which often focus on what governments should do to protect citizens during emergencies but fail to outline how governments should prepare for an emergency operation. The study concludes that GCPs contribute to increased resilience among the public sector in terms of robustness, redundancy, resourcefulness and rapidity.Practical implicationsThis paper includes implications for the development and improvement of a GCP's operational guideline.Originality/valueThis research fulfills an identified need to investigate the effectiveness of a GCP for resilience in the public sector and how to improve its operation using concepts of CAS.


2014 ◽  
Vol 37 (6) ◽  
pp. 563-564 ◽  
Author(s):  
Tobias A. Mattei

AbstractIn self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.


2013 ◽  
Vol 5 (2) ◽  
pp. 140-153
Author(s):  
Patrick Schotanus

The aim of this paper is to contribute to Jung's later work, with a particular focus on the numerical archetypes viewed from an investor's perspective. It attempts to achieve this via a three-pronged approach. First, placing complex psychology in the framework of complexity theory allows a robust acknowledgement and treatment of ‘elusive’ macroscopic properties, i.e. archetypal dynamics, involved in the ordering of a mind as a complex adaptive system. Second, modern insights in number sense (the direct intuition of what numbers mean) provide neuroscientific support for numerical archetypes and clarify their primacy. Third, this paper points to the empirical relevance of numerical archetypes in price discovery, the self-organizing principle of the capital markets (which allocate resources in modern society). The resulting proposition is that the (collective) mind's unconscious and conscious forces can be considered as ‘intelligent’ agents. The competition between these two domains provides the necessary condition to endogenously generate innovative outcomes, the essential capability of complex adaptive systems. According to this view producing such adaptive novelty is achieved in the form of intuitive insights and imagination, which result in a vast array of symbols, e.g. prices in the case of the market's mind.


Urban Science ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 61
Author(s):  
Annetta Burger ◽  
William G. Kennedy ◽  
Andrew Crooks

Increasingly urbanized populations and climate change have shifted the focus of decision makers from economic growth to the sustainability and resilience of urban infrastructure and communities, especially when communities face multiple hazards and need to recover from recurring disasters. Understanding human behavior and its interactions with built environments in disasters requires disciplinary crossover to explain its complexity, therefore we apply the lens of complex adaptive systems (CAS) to review disaster studies across disciplines. Disasters can be understood to consist of three interacting systems: (1) the physical system, consisting of geological, ecological, and human-built systems; (2) the social system, consisting of informal and formal human collective behavior; and (3) the individual actor system. Exploration of human behavior in these systems shows that CAS properties of heterogeneity, interacting subsystems, emergence, adaptation, and learning are integral, not just to cities, but to disaster studies and connecting them in the CAS framework provides us with a new lens to study disasters across disciplines. This paper explores the theories and models used in disaster studies, provides a framework to study and explain disasters, and discusses how complex adaptive systems can support theory building in disaster science for promoting more sustainable and resilient cities.


Author(s):  
Asif Khan ◽  
Khursheed Aurangzeb ◽  
Sheraz Aslam ◽  
Musaed Alhussein

Megacities are complex systems facing the challenges of overpopulation, poor urban design and planning, poor mobility and public transport, poor governance, climate change issues, poor sewerage and water infrastructure, waste and health issues, and unemployment. Smart cities have emerged to address these challenges by making the best use of space and resources for the benefit of citizens. A smart city model views the city as a complex adaptive system consisting of services, resources, and citizens that learn through interaction and change in both the spatial and temporal domains. The characteristics of dynamic development and complexity are key issues for city planners that require a new systematic and modeling approach. Multiscale modeling (MM) is an approach that can be used to better understand complex adaptive systems. The MM aims to solve complex problems at different scales, i.e., micro, meso, and macro, to improve system efficiency and mitigate computational complexity and cost. In this paper, we present an overview of MM in smart cities. First, this study discusses megacities, their current challenges, and their emergence to smart cities. Then, we discuss the need of MM in smart cities and its emerging applications. Finally, the study highlights current challenges and future directions related to MM in smart cities, which provide a roadmap for the optimized operation of smart city systems.


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