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Systems, Volume 7, Issue 4 (December 2019) – 9 articles

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Open AccessArticle
Theoretical Foundations for Preference Representation in Systems Engineering
Systems 2019, 7(4), 55; https://doi.org/10.3390/systems7040055 - 12 Dec 2019
Viewed by 436
Abstract
The realization of large-scale complex engineered systems is contingent upon satisfaction of the preferences of the stakeholder. With numerous decisions being involved in all the aspects of the system lifecycle, from conception to disposal, it is critical to have an explicit and rigorous [...] Read more.
The realization of large-scale complex engineered systems is contingent upon satisfaction of the preferences of the stakeholder. With numerous decisions being involved in all the aspects of the system lifecycle, from conception to disposal, it is critical to have an explicit and rigorous representation of stakeholder preferences to be communicated to key personnel in the organizational hierarchy. Past work on stakeholder preference representation and communication in systems engineering has been primarily requirement-driven. More recent value-based approaches still do not offer a rigorous framework on how to represent stakeholder preferences but assume that an overarching value function that can precisely capture stakeholder preferences exists. This article provides a formalism based on modal preference logic to aid in rigorous representation and communication of stakeholder preferences. Formal definitions for the different types of stakeholder preferences encountered in a systems engineering context are provided in addition to multiple theorems that improve the understanding of the relationship between stakeholder preferences and the solution space. Full article
(This article belongs to the collection Systems Engineering)
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Open AccessFeature PaperArticle
A Governance Perspective for System-of-Systems
Systems 2019, 7(4), 54; https://doi.org/10.3390/systems7040054 - 09 Dec 2019
Viewed by 503
Abstract
The operating landscape of 21st century systems is characteristically ambiguous, emergent, and uncertain. These characteristics affect the capacity and performance of engineered systems/enterprises. In response, there are increasing calls for multidisciplinary approaches capable of confronting increasingly ambiguous, emergent, and uncertain systems. System of [...] Read more.
The operating landscape of 21st century systems is characteristically ambiguous, emergent, and uncertain. These characteristics affect the capacity and performance of engineered systems/enterprises. In response, there are increasing calls for multidisciplinary approaches capable of confronting increasingly ambiguous, emergent, and uncertain systems. System of Systems Engineering (SoSE) is an example of such an approach. A key aspect of SoSE is the coordination and the integration of systems to enable ‘system-of-systems’ capabilities greater than the sum of the capabilities of the constituent systems. However, there is a lack of qualitative studies exploring how coordination and integration are achieved. The objective of this research is to revisit SoSE utility as a potential multidisciplinary approach and to suggest ‘governance’ as the basis for enabling ‘system-of-systems’ coordination and integration. In this case, ‘governance’ is concerned with direction, oversight, and accountability of ‘system-of-systems.’ ‘Complex System Governance’ is a new and novel basis for improving ‘system-of-system’ performance through purposeful design, execution, and evolution of essential metasystem functions.’ Full article
(This article belongs to the Special Issue Advances in the Systems Sciences 2018)
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Open AccessArticle
Simulating a Watershed-Scale Strategy to Mitigate Drought, Flooding, and Sediment Transport in Drylands
Systems 2019, 7(4), 53; https://doi.org/10.3390/systems7040053 - 28 Nov 2019
Viewed by 550
Abstract
Drylands today are facing a landscape-scale water storage problem. Throughout the increasingly arid Southwest of the United States, vegetation loss in upland watersheds is leading to floods that scour soils and transport sediment that clogs downstream riparian areas and agricultural infrastructure. The resulting [...] Read more.
Drylands today are facing a landscape-scale water storage problem. Throughout the increasingly arid Southwest of the United States, vegetation loss in upland watersheds is leading to floods that scour soils and transport sediment that clogs downstream riparian areas and agricultural infrastructure. The resulting higher flow energies and diminished capacity to infiltrate flood flows are depleting soil water storage across the landscape, negatively impacting agriculture and ecosystems. Land and water managers face challenges to reverse the trends due to the complex interacting social and biogeophysical root causes. Presented here is an integrative system dynamics model that simulates innovative and transformative management scenarios. These scenarios include the natural and hydro-social processes and feedback dynamics critical for achieving long-term mitigation of droughts, flooding, and sediment transport. This model is a component of the Flood Flow Connectivity to the Landscape framework, which integrates spatial and hydrologic process models. Scenarios of support and collaboration for land management innovations are simulated to connect flood flow to the floodplains throughout the watershed to replenish soil storage and shallow groundwater aquifers across regional scales. The results reveal the management policy levers and trade-off balances critical for restoring management and water storage capacity to the system for long-term resilience. Full article
(This article belongs to the Special Issue System Dynamics: Insights and Policy Innovation)
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Open AccessCommunication
Sustainable Feedbacks of Colombian Paramos Involving Livestock, Agricultural Activities, and Sustainable Development Goals of the Agenda 2030
Systems 2019, 7(4), 52; https://doi.org/10.3390/systems7040052 - 28 Nov 2019
Viewed by 542
Abstract
Colombian mountain Páramos are considered natural areas with a very important role for human life. Páramos provide, both in mountain and lowland areas, a multitude of ecosystem services which start from vegetation to soil sustainability. The sustainability of Páramos is however impaired by [...] Read more.
Colombian mountain Páramos are considered natural areas with a very important role for human life. Páramos provide, both in mountain and lowland areas, a multitude of ecosystem services which start from vegetation to soil sustainability. The sustainability of Páramos is however impaired by several anthropogenic activities, including agricultural and livestock practices. A system thinking approach was applied in this work to improve the systemic understanding of factors affecting sustainability and resilience of Páramos agro-ecosystems. Interdisciplinary literature evidences were summarized and conceptually analyzed in order to develop causal loop diagrams of Páramo system structures allowing describing the main feedback loops involving (involved in/connecting) the Páramo ecosystem and driving its sustainability. From the causal diagram analysis few insights to maintain the human presence in Páramos arose. The system analysis highlights that human presence in Páramos should be stimulated, avoiding agriculture and livestock activities as the main income source. Particularly, social interactions, education on the Páramos environmental and relevance of agricultural practices to foster ecosystem services and multiple rentable economic activities should be enhanced. The study also includes the role of the government in providing the Páramo inhabitants with payments for ecosystem services and environmental education aimed to boost sustainability. Sustainable Páramo management will apply specific leverages on the system to reach Sustainable Development Goals 6 (water), 8 (economic growth, employment and work), 13 (climate change), and 15 (sustainable use of terrestrial ecosystems) of the Agenda 2030. Full article
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Open AccessArticle
Nonclassical Systemics of Quasicoherence: From Formal Properties to Representations of Generative Mechanisms. A Conceptual Introduction to a Paradigm-Shift
Systems 2019, 7(4), 51; https://doi.org/10.3390/systems7040051 - 28 Nov 2019
Viewed by 466
Abstract
In this article, we consider how formal models and properties of emergence, e.g., long-range correlations, power laws, and self-similarity are usually platonically considered to represent the essence of the phenomenon, more specifically, their acquired properties, e.g., coherence, and not their generative mechanisms. Properties [...] Read more.
In this article, we consider how formal models and properties of emergence, e.g., long-range correlations, power laws, and self-similarity are usually platonically considered to represent the essence of the phenomenon, more specifically, their acquired properties, e.g., coherence, and not their generative mechanisms. Properties are assumed to explain, rather than represent, real processes of emergence. Conversely, real phenomenological processes are intended to be approximations or degenerations of their essence. By contrast, here, we consider the essence as a simplification of the phenomenological complexity. It is assumed to be acceptable that such simplification neglects several aspects (e.g., incompleteness, inhomogeneities, instabilities, irregularities, and variations) of real phenomena in return for analytical tractability. Within this context, such a trade-off is a kind of reductionism when dealing with complex phenomena. Methodologically, we propose a paradigmatic change for systems science equivalent to the one that occurred in Physics from object to field, namely, a change from interactional entities to domains intended as extensions of fields, or multiple fields, as it were. The reason to introduce such a paradigm shift is to make nonidealist approaches suitable for dealing with more realistic quasicoherence, when the coherence does not consistently apply to all the composing entities, but rather, different forms of coherence apply. As a typical general interdisciplinary case, we focus on so-called collective behaviors. The goal of this paper is to introduce the concepts of domain and selection mechanisms which are suitable to represent the generative mechanisms of quasicoherence of collective behavior. Domains are established by self-tracking entities such as financial or are effectively GPS-detectable. Such domains allow the profiling of collective behavior. Selection mechanisms are based on learning techniques or cognitive approaches for social systems. Full article
Open AccessArticle
Dominant Factors for an Effective Selection System: An Australian Education Sector Perspective
Systems 2019, 7(4), 50; https://doi.org/10.3390/systems7040050 - 01 Nov 2019
Viewed by 602
Abstract
With the latest advancements in information technologies, many organisations expect systems to provide effective support in the recruitment process and decision making. However, there is a lack of clarity on the dominant factors required for an effective recruitment system which can influence business [...] Read more.
With the latest advancements in information technologies, many organisations expect systems to provide effective support in the recruitment process and decision making. However, there is a lack of clarity on the dominant factors required for an effective recruitment system which can influence business outcomes. This paper aimed to identify the predominant factors in the employee selection process and the use of a management system for decision support. The empirical study consisted of a qualitative survey of 74 samples and a quantitative survey of 204 individual participants from 17 organisations coming from technical and further education (TAFE)/dual education (higher education and vocational education) sector members of the Victorian TAFE Association in Australia. Using commonly adopted exploratory factor analysis (EFA) of 38 variables, the data triangulation of the qualitative and quantitative analysis resulted in conformance of five dominant factors under three themes. We believe the results of the study offer actionable suggestions in developing an effective recruitment system and furthers the research in this field of study. Full article
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Open AccessFeature PaperArticle
A System Dynamics Model Examining Alternative Wildfire Response Policies
Systems 2019, 7(4), 49; https://doi.org/10.3390/systems7040049 - 04 Oct 2019
Viewed by 801
Abstract
In this paper, we develop a systems dynamics model of a coupled human and natural fire-prone system to evaluate changes in wildfire response policy. A primary motivation is exploring the implications of expanding the pace and scale of using wildfires as a forest [...] Read more.
In this paper, we develop a systems dynamics model of a coupled human and natural fire-prone system to evaluate changes in wildfire response policy. A primary motivation is exploring the implications of expanding the pace and scale of using wildfires as a forest restoration tool. We implement a model of a forested system composed of multiple successional classes, each with different structural characteristics and propensities for burning at high severity. We then simulate a range of alternative wildfire response policies, which are defined as the combination of a target burn rate (or inversely, the mean fire return interval) and a predefined transition period to reach the target return interval. We quantify time paths of forest successional stage distributions, burn severity, and ecological departure, and use departure thresholds to calculate how long it would take various policies to restore forest conditions. Furthermore, we explore policy resistance where excessive rates of high burn severity in the policy transition period lead to a reversion to fire exclusion policies. Establishing higher burn rate targets shifted vegetation structural and successional classes towards reference conditions and suggests that it may be possible to expand the application of wildfires as a restoration tool. The results also suggest that managers may be best served by adopting strategies that define aggressive burn rate targets but by implementing policy changes slowly over time. Full article
(This article belongs to the Special Issue System Dynamics: Insights and Policy Innovation)
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Open AccessArticle
Systems Thinking Using SSM and TRIZ for Stakeholder Engagement in Infrastructure Megaprojects
Systems 2019, 7(4), 48; https://doi.org/10.3390/systems7040048 - 26 Sep 2019
Viewed by 822
Abstract
Infrastructure megaprojects straddle multiple stakeholder boundaries who have an interest in the project and are affected by the project. Multiple papers in the literature stress the need for holistic approaches to stakeholder engagement, as existing approaches only address the concerns of the noisy [...] Read more.
Infrastructure megaprojects straddle multiple stakeholder boundaries who have an interest in the project and are affected by the project. Multiple papers in the literature stress the need for holistic approaches to stakeholder engagement, as existing approaches only address the concerns of the noisy stakeholders. This research proposes an innovative approach in which Soft Systems Methodology (SSM) is used for understanding stakeholder concerns, complemented by the use of Theory of Inventive Problem Solving (TRIZ) for identifying innovative solutions to address conflicting stakeholder goals. The researchers simulated the stakeholder engagement of the Coimbatore metro rail project, in India, through a workshop setting in a classroom to check the feasibility of this approach for stakeholder engagement. The 15 participants of the workshop were divided into four groups representing different stakeholders of the project. Data was collected through participant observations by the authors and oral feedback from the participants. The results show that while SSM helped to capture the concerns and goals of each stakeholder, TRIZ helped to identify and dissolve conflicts among these goals through innovative solutions. The theoretical, practical and pedagogical contributions are highlighted. Full article
(This article belongs to the Special Issue Systems Thinking in Project Management)
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Open AccessArticle
A System Dynamics Modeling Support System Based on Computational Intelligence
Systems 2019, 7(4), 47; https://doi.org/10.3390/systems7040047 - 25 Sep 2019
Viewed by 903
Abstract
System dynamics (SD) is a complex systems modeling and simulation approach with wide ranging applications in various science and engineering disciplines. While subject matter experts lead most of the model building, recent advances have attempted to bring system dynamics closer to fast growing [...] Read more.
System dynamics (SD) is a complex systems modeling and simulation approach with wide ranging applications in various science and engineering disciplines. While subject matter experts lead most of the model building, recent advances have attempted to bring system dynamics closer to fast growing fields such as data sciences. This may prove promising for the development of novel support methods that augment human cognition and improve efficiencies in the model building process. A few different directions have been explored recently to support individual modeling stages, such as the generation of model structure, model calibration and policy optimization. However, an integrated approach that supports across the board modeling process is still missing. In this paper, a prototype integrated modeling support system is presented for the purpose of supporting the modelers at each stage of the process. The proposed support system facilitates data-driven inferring of causal loop diagrams (CLDs), stock-flow diagrams (SFDs), model equations and the estimation of model parameters using computational intelligence (CI) techniques. The ultimate goal of the proposed system is to support the construction of complex models, where the human power is not enough. With this goal in mind, we demonstrate the working and utility of the proposed support system. We have used two well-known synthetic reality case studies with small models from the system dynamics literature, in order to verify the support system performance. The experimental results showed the effectiveness of the proposed support system to infer close model structures to target models directly from system time-series observations. Future work will focus on improving the support system so that it can generate complex models on a large scale. Full article
(This article belongs to the collection System Dynamics)
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