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Systems
Special Issues
Systems Approaches and Tools for Managing Complexity
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Systems Approaches and Tools for Managing Complexity

A special issue of Systems (ISSN 2079-8954).

Deadline for manuscript submissions: closed (15 May 2017) | Viewed by 79900

Special Issue Editors

Dr. Nam Nguyen

E-Mail Website
Guest Editor
1. Director Australia and Southeast Asia, Malik Institute, St. Gallen, Switzerland
2. Hon. Fellow, The University of Adelaide Business School, Adelaide, Australia
Interests: systems thinking; Malik SuperSyntegration (MSS); Malik management systems; systems design and complexity management; systems-based evolutionary learning laboratory (ELLab) framework; systems tools (causal loop diagrams, systems archetypes, Bayesian belief network, sensitivity model); integration; community-based research; participatory approaches; user-friendly decision support systems (crop choice, ELLab, Think2Impact); academic and executive training (including PhD supervision and MBA teaching)
Dr. Constantin Malik

E-Mail Website
Guest Editor
Exec. Director Global Relations and Development, Malik Institute, St. Gallen, Switzerland
Interests: systems thinking; management cybernetics and bionics; systems modelling; systems design and complexity management; systems structure; city and urban dynamics; crowd psychology and crowd dynamics
Dr. Thanh V. Nguyen

E-Mail Website
Guest Editor
Deputy Minister, Ministry of Public Security, Vietnam
Interests: systems thinking; economics; law; industrial economics management; integrated coastal management; marine spatial planning; conservation and management of biosphere reserves; urban mobility planning; sustainable development; green city; public security; governance and leadership
Mr. Tuan Ha

E-Mail Website
Co-Guest Editor
Researcher, Systems Design and Complexity Management Alliance, The University of Adelaide Business School, Adelaide, SA 5005, Australia
Interests: community development; decision support systems; participatory action research; system dynamics modelling; systems thinking; transformative learning

Special Issue Information

Dear Colleagues,

We are living in an increasingly complex world, in which all economic, social, environmental, cultural and political factors and processes are evidently interconnected. Traditional problem-solving approaches through simple linear thinking and “quick fixes” that solve issues in isolation have posed various shortcomings, including failures, and even counterproductive consequences.

Complex problems in our constantly changing world require better approaches and supporting tools to help unravel such complexity, understand the context and identify interrelationships among different factors surrounding an issue under consideration. This process enables the identification of the root causes of a visible problem, systemic interplays among different factors and subsystems for developing informed, viable, feasible and sustainable solutions.

Recently, systems approaches and systems tools have been successfully applied in various areas and disciplines such as complexity management, community operational research, project management, education, business, environment, health, agriculture, agribusiness, governance, and sustainable development, etc. The successes have proven the value and validity of systems approaches and tools in coping with complexity around the world.

This Special Issue aims to update the use of both existing and emerging systems approaches and relevant tools in managing complexity in any area of interest.

The Special Issue seeks contributions that focus on, but not limited to, the followings:

  • Theoretical frameworks in dealing with complexity;
  • Systems thinking and problem structuring methods;
  • Utilising systems tools in solving complex problems;
  • Systems dynamics modelling and simulation.

We welcome papers that present approaches, frameworks, models, and case studies using systems approaches or tools in any area of application

Dr. Nam Nguyen
Dr. Constantin Malik
Dr. Thanh V. Nguyen
Guest Editors

Dr. Tuan Ha
Co-Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Complex problems
  • Systems design
  • Complexity management
  • Complexity sciences
  • Cybernetics
  • Management systems
  • Problem structuring
  • Simulation
  • Systems approaches/theories
  • System dynamics
  • Systems tools

Published Papers (5 papers)

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Research

7306 KiB  
Article
A Method for Simplification of Complex Group Causal Loop Diagrams Based on Endogenisation, Encapsulation and Order-Oriented Reduction
by Vladimír Bureš
Systems 2017, 5(3), 46; https://doi.org/10.3390/systems5030046 - 14 Jul 2017
Cited by 47 | Viewed by 25774
Abstract
Growing complexity represents an issue that can be identified in various disciplines. In system dynamics, causal loop diagrams are used for capturing dynamic nature of modelled systems. Increasing complexity of developed diagrams is associated with the tendency to include more variables into a [...] Read more.
Growing complexity represents an issue that can be identified in various disciplines. In system dynamics, causal loop diagrams are used for capturing dynamic nature of modelled systems. Increasing complexity of developed diagrams is associated with the tendency to include more variables into a model and thus make it more realistic and improve its value. This is even multiplied during group modelling workshops where several perspectives are articulated, shared and complex diagrams developed. This process easily generates complex diagrams that are difficult or even impossible to be comprehended by individuals. As there is a lack of available methods that would help users to cope with growing complexity, this manuscript suggests an original method. The proposed method systematically helps to simplify the complex causal loop diagrams. It is based on three activities iteratively applied during particular steps: endogenisation, encapsulation and order-oriented reduction. Two case studies are used to explain method details, prove its applicability and highlight added value. Case studies include the simplification of both original group causal loop diagram, and group diagram adapted from a study already published in a prestigious journal. Although the presented method has its own limitations, meaningfulness of its application in practice is verified. The method can help to cope with the complexity in any domain, in which causal loop diagrams are used. Full article
(This article belongs to the Special Issue Systems Approaches and Tools for Managing Complexity)
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1031 KiB  
Article
Ontology-Based Big Data Management
by Bastian Eine, Matthias Jurisch and Werner Quint
Systems 2017, 5(3), 45; https://doi.org/10.3390/systems5030045 - 06 Jul 2017
Cited by 30 | Viewed by 12887
Abstract
Big data management is no longer an issue for large enterprises only; it has also become a challenge for small and middle-sized enterprises, too. Today, enterprises have to handle business data and processes of increasing complexity that are almost entirely electronic in nature, [...] Read more.
Big data management is no longer an issue for large enterprises only; it has also become a challenge for small and middle-sized enterprises, too. Today, enterprises have to handle business data and processes of increasing complexity that are almost entirely electronic in nature, regardless of enterprises’ size. Enterprises’ information systems need functions based on specific technologies to be able to reduce and interpret the complexity of business data and processes. This paper pursues the question: how can state-of-the-art information systems be improved by the use of semantic technologies, and particularly ontologies? For this purpose, three use cases of information systems that could be improved are described, and approaches based on semantic technologies and ontologies are proposed. The selected use cases relate to data integration, data quality, and business process integration. Full article
(This article belongs to the Special Issue Systems Approaches and Tools for Managing Complexity)
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2109 KiB  
Article
A Multi-Methodological Approach to Complex Problem Solving: The Case of Serbian Enterprise
by Dejana Zlatanović
Systems 2017, 5(2), 40; https://doi.org/10.3390/systems5020040 - 30 May 2017
Cited by 4 | Viewed by 8665
Abstract
Increasing complexity and diversity of management problems in modern enterprises requires the increasing diversity of models, methods, and methodologies. In creatively dealing with these complex, changeable and multidimensional management problems, i.e., problem situations, different systems methodologies for problem situations, structuring have been developed. [...] Read more.
Increasing complexity and diversity of management problems in modern enterprises requires the increasing diversity of models, methods, and methodologies. In creatively dealing with these complex, changeable and multidimensional management problems, i.e., problem situations, different systems methodologies for problem situations, structuring have been developed. Since no methodology is able to explore all aspects of the complex problems in enterprises, the topic of this paper is a multi-methodology approach that implies combining selected systems methodologies (Strategic Assumptions Surfacing and Testing, Team Syntegrity and Organizational Cybernetics) within a particular intervention. Therefore, research in the paper is relied on Critical Systems Thinking as a conceptual framework for combined use of systems methodologies. The paper aims to demonstrate how mixing the selected systems methodologies and tools can help managers in solving complex problems, such as the issues of strategy formulation and implementation in enterprises. Accordingly, combining these methodologies to support strategy formulation and implementation is applied to a Serbian enterprise. Full article
(This article belongs to the Special Issue Systems Approaches and Tools for Managing Complexity)
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4432 KiB  
Article
Application of System Dynamics to Evaluate the Social and Economic Benefits of Infrastructure Projects
by Tiep Nguyen, Stephen Cook and Vernon Ireland
Systems 2017, 5(2), 29; https://doi.org/10.3390/systems5020029 - 29 Mar 2017
Cited by 31 | Viewed by 20984
Abstract
Cost-Benefit Analysis (CBA) is often employed to inform decision makers about the desirability of transport infrastructure investment options. One of the main limitations of traditional CBA approaches is that they do not provide a dynamic view that explicitly illustrates the cost and benefit [...] Read more.
Cost-Benefit Analysis (CBA) is often employed to inform decision makers about the desirability of transport infrastructure investment options. One of the main limitations of traditional CBA approaches is that they do not provide a dynamic view that explicitly illustrates the cost and benefit relationships between component entities over time. This paper addresses this issue by describing a System Dynamics (SD) approach that can perform transport infrastructure CBA through the application of systems thinking to develop a causal-loop model that can subsequently be operationalised into an executable stock-and-flow model. Execution of this model readily enables sensitivity analysis of infrastructure investment options and visualisation of the cost-benefit behaviour of each variant over time. The utility of the approach is illustrated through a case study, the Co Chien Bridge project in Vietnam, using a model that incorporates conventional economic metrics and factors that measure indirect project benefits, such as impact on gross domestic product, unemployment rate, and total taxes gained from affected economic sectors. Full article
(This article belongs to the Special Issue Systems Approaches and Tools for Managing Complexity)
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2581 KiB  
Article
Designing Computer-Supported Complex Systems Curricula for the Next Generation Science Standards in High School Science Classrooms
by Susan A. Yoon, Emma Anderson, Eric Klopfer, Jessica Koehler-Yom, Josh Sheldon, Ilana Schoenfeld, Daniel Wendel, Hal Scheintaub, Murat Oztok, Chad Evans and Sao-Ee Goh
Systems 2016, 4(4), 38; https://doi.org/10.3390/systems4040038 - 03 Dec 2016
Cited by 32 | Viewed by 10857
Abstract
We present a curriculum and instruction framework for computer-supported teaching and learning about complex systems in high school science classrooms. This work responds to a need in K-12 science education research and practice for the articulation of design features for classroom instruction that [...] Read more.
We present a curriculum and instruction framework for computer-supported teaching and learning about complex systems in high school science classrooms. This work responds to a need in K-12 science education research and practice for the articulation of design features for classroom instruction that can address the Next Generation Science Standards (NGSS) recently launched in the USA. We outline the features of the framework, including curricular relevance, cognitively rich pedagogies, computational tools for teaching and learning, and the development of content expertise, and provide examples of how the framework is translated into practice. We follow this up with evidence from a preliminary study conducted with 10 teachers and 361 students, aimed at understanding the extent to which students learned from the activities. Results demonstrated gains in students’ complex systems understanding and biology content knowledge. In interviews, students identified influences of various aspects of the curriculum and instruction framework on their learning. Full article
(This article belongs to the Special Issue Systems Approaches and Tools for Managing Complexity)
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