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Systems, Volume 3, Issue 4 (December 2015) – 10 articles , Pages 152-398

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Article
An Examination of the Influence of Household Financial Decision Making on the US Housing Market Crisis
Systems 2015, 3(4), 378-398; https://doi.org/10.3390/systems3040378 - 08 Dec 2015
Cited by 1 | Viewed by 3901
Abstract
This paper investigates the impact of what the extant literature has come to view as some of the major causes of the 2007 US housing market crisis. In particular we investigate the hypothesized effect of, lax financial regulations, the “savings glut” that is [...] Read more.
This paper investigates the impact of what the extant literature has come to view as some of the major causes of the 2007 US housing market crisis. In particular we investigate the hypothesized effect of, lax financial regulations, the “savings glut” that is invested in the US from abroad, government support for increased home ownership, rising homeowners’ equity due to the real-estate boom, expansionary monetary policy, and bankruptcy reform. We examine how these hypothesized causes, working through household and institutional level decision-making, based on information availability and incentives, influenced the outcomes in the market for homes. Using a system dynamics model of household finance, we overlay the hypothesized causes chronologically to extrapolate their real-world simultaneous impact and test the hypothesis that they could have together led to the crisis, by simulating and checking against observed data. We find that with the exception of lax financial regulations, each cause by itself provides only a partial explanation of the crisis. Interestingly, the controversial expansionary monetary policy of the Federal Reserve, blamed by some for fueling the crisis, actually prevents the housing market boom from becoming too large. However on the downside, it discourages household savings and causes the fall in home prices to be deeper, due to weak household finances that result from low savings. We confront our model’s assumptions and outcomes with US economic data. We find our model assumptions are justified and simulation results are strongly supported by the data. Full article
(This article belongs to the Special Issue System Dynamics: Insights and Policy Innovation)
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Article
A Modular Modelling Framework for Hypotheses Testing in the Simulation of Urbanisation
Systems 2015, 3(4), 348-377; https://doi.org/10.3390/systems3040348 - 27 Nov 2015
Cited by 12 | Viewed by 3586
Abstract
In this paper, we present a modelling experiment developed to study systems of cities and processes of urbanisation in large territories over long time spans. Building on geographical theories of urban evolution, we rely on agent-based models to 1) formalise complementary and alternative [...] Read more.
In this paper, we present a modelling experiment developed to study systems of cities and processes of urbanisation in large territories over long time spans. Building on geographical theories of urban evolution, we rely on agent-based models to 1) formalise complementary and alternative hypotheses of urbanisation and 2) explore their ability to simulate observed patterns in a virtual laboratory. The paper is therefore divided into two sections : an overview of the mechanisms implemented to represent competing hypotheses used to simulate urban evolution; and an evaluation of the resulting model structures in their ability to simulate—efficiently and parsimoniously—a system of cities (between 1000 and 2000 cities in the Former Soviet Union) over several periods of time (before and after the crash of the USSR). We do so using a modular framework of model-building and evolutionary algorithms for the calibration of several model structures. This project aims at tackling equifinality in systems dynamics by confronting different mechanisms with similar evaluation criteria. It enables the identification of the best-performing models with respect to the chosen criteria by scanning automatically the parameter space along with the space of model structures (the different combinations of mechanisms). Full article
(This article belongs to the Special Issue Agent-Based Modelling of City Systems)
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Article
Feral Information Systems Creation as Sensemaking
Systems 2015, 3(4), 330-347; https://doi.org/10.3390/systems3040330 - 26 Nov 2015
Cited by 5 | Viewed by 3175
Abstract
This paper discussed the role of actors in creating their own sensemaking devices as Feral Information Systems. In particular, we explore how Feral Information Systems (FIS) are actually a creative way to work around complex information systems and need to be acknowledged as [...] Read more.
This paper discussed the role of actors in creating their own sensemaking devices as Feral Information Systems. In particular, we explore how Feral Information Systems (FIS) are actually a creative way to work around complex information systems and need to be acknowledged as such. We use the sensemaking framework to explore how new FIS are developed as a sensemaking device in order assist in daily important tasks. We conclude with suggestions for future research. Full article
(This article belongs to the Special Issue Enterprise Resource Planning Systems)
Article
The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach
Systems 2015, 3(4), 309-329; https://doi.org/10.3390/systems3040309 - 20 Nov 2015
Cited by 11 | Viewed by 3476
Abstract
This work addresses the spread of a disease within an urban system, definedas a network of interconnected cities. The first step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE) Susceptible-Infected-Recovered (SIR) systems exploiting populations [...] Read more.
This work addresses the spread of a disease within an urban system, definedas a network of interconnected cities. The first step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE) Susceptible-Infected-Recovered (SIR) systems exploiting populations onnodes and flows on edges (so-called metapopulational model), and a hybrid one, couplingODE SIR systems on nodes and agents traveling on edges. Under homogeneous conditions(mean field approximation), this comparison leads to similar results on the outputs on whichwe focus (the maximum intensity of the epidemic, its duration and the time of the epidemicpeak). However, when it comes to setting up epidemic control strategies, results rapidlydiverge between the two approaches, and it appears that the full macroscopic model is notcompletely adapted to these questions. In this paper, we focus on some control strategies,which are quarantine, avoidance and risk culture, to explore the differences, advantages anddisadvantages of the two models and discuss the importance of being hybrid when modelingand simulating epidemic spread at the level of a whole urban system. Full article
(This article belongs to the Special Issue Agent-Based Modelling of City Systems)
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Article
Exploring Tradeoffs in Demand-Side and Supply-Side Management of Urban Water Resources Using Agent-Based Modeling and Evolutionary Computation
Systems 2015, 3(4), 287-308; https://doi.org/10.3390/systems3040287 - 13 Nov 2015
Cited by 8 | Viewed by 3665
Abstract
Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the [...] Read more.
Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the performance of demand-side strategies, the participation and water use adaptations of consumers should be simulated. In this study, a Complex Adaptive Systems (CAS) framework is developed to simulate consumer agents that change their consumption to affect the withdrawal from the water supply system, which, in turn influences operational policies and long-term resource planning. Agent-based models are encoded to represent consumers and a policy maker agent and are coupled with water resources system simulation models. The CAS framework is coupled with an evolutionary computation-based multi-objective methodology to explore tradeoffs in cost, inconvenience to consumers, and environmental impacts for both supply-side and demand-side strategies. Decisions are identified to specify storage levels in a reservoir that trigger: (1) increases in the volume of water pumped through inter-basin transfers from an external reservoir; and (2) drought stages, which restrict the volume of water that is allowed for residential outdoor uses. The proposed methodology is demonstrated for Arlington, Texas, water supply system to identify non-dominated strategies for an historic drought decade. Results demonstrate that pumping costs associated with maximizing environmental reliability exceed pumping costs associated with minimizing restrictions on consumer water use. Full article
(This article belongs to the Special Issue Agent-Based Modelling of City Systems)
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Article
The Effect of a Structured Method on Mental Model Accuracy and Performance in a Complex Task
Systems 2015, 3(4), 264-286; https://doi.org/10.3390/systems3040264 - 13 Nov 2015
Cited by 5 | Viewed by 3636
Abstract
In comparison to their performance with normative standards or even simple heuristics, humans do not perform well in complex decision-making. The application of systems thinking to help people to understand and handle interdependent and complex systems is proposed as a means of improving [...] Read more.
In comparison to their performance with normative standards or even simple heuristics, humans do not perform well in complex decision-making. The application of systems thinking to help people to understand and handle interdependent and complex systems is proposed as a means of improving this poor performance. The aim of this study is to investigate the effect of a generic systems thinking method, i.e., a structured method, on performance. A laboratory experiment was conducted using a dynamic and complex simulation task. The results demonstrated that subjects provided with a structured method achieved a higher performance. In addition, mental model accuracy had a significant effect on performance, as already shown by several previous studies. The results of our study provide a way of teaching subjects how to improve their performance when coping with complex systems in general. This has implications for education in the fields of complex systems and system dynamics. Full article
(This article belongs to the Special Issue Dynamic Decision Making in Controlled Experiments)
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Article
Supporting Student Learning in Computer Science Education via the Adaptive Learning Environment ALMA
Systems 2015, 3(4), 237-263; https://doi.org/10.3390/systems3040237 - 12 Oct 2015
Cited by 1 | Viewed by 3549
Abstract
This study presents the ALMA environment (Adaptive Learning Models from texts and Activities). ALMA supports the processes of learning and assessment via: (1) texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2) activities corresponding to [...] Read more.
This study presents the ALMA environment (Adaptive Learning Models from texts and Activities). ALMA supports the processes of learning and assessment via: (1) texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2) activities corresponding to different levels of comprehension which prompt the student to practically implement different text-reading strategies, with the recommended activity sequence adapted to the student’s learning style; (3) an overall framework for informing, guiding, and supporting students in performing the activities; and; (4) individualized support and guidance according to student specific characteristics. ALMA also, supports students in distance learning or in blended learning in which students are submitted to face-to-face learning supported by computer technology. The adaptive techniques provided via ALMA are: (a) adaptive presentation and (b) adaptive navigation. Digital learning material, in accordance with the text comprehension model described by Kintsch, was introduced into the ALMA environment. This material can be exploited in either distance or blended learning. Full article
(This article belongs to the Special Issue Adaptive Educational Technology Systems)
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Article
Approaches to Learning to Control Dynamic Uncertainty
Systems 2015, 3(4), 211-236; https://doi.org/10.3390/systems3040211 - 10 Oct 2015
Cited by 6 | Viewed by 3563
Abstract
In dynamic environments, when faced with a choice of which learning strategy to adopt, do people choose to mostly explore (maximizing their long term gains) or exploit (maximizing their short term gains)? More to the point, how does this choice of learning strategy [...] Read more.
In dynamic environments, when faced with a choice of which learning strategy to adopt, do people choose to mostly explore (maximizing their long term gains) or exploit (maximizing their short term gains)? More to the point, how does this choice of learning strategy influence one’s later ability to control the environment? In the present study, we explore whether people’s self-reported learning strategies and levels of arousal (i.e., surprise, stress) correspond to performance measures of controlling a Highly Uncertain or Moderately Uncertain dynamic environment. Generally, self-reports suggest a preference for exploring the environment to begin with. After which, those in the Highly Uncertain environment generally indicated they exploited more than those in the Moderately Uncertain environment; this difference did not impact on performance on later tests of people’s ability to control the dynamic environment. Levels of arousal were also differentially associated with the uncertainty of the environment. Going beyond behavioral data, our model of dynamic decision-making revealed that, in actual fact, there was no difference in exploitation levels between those in the highly uncertain or moderately uncertain environments, but there were differences based on sensitivity to negative reinforcement. We consider the implications of our findings with respect to learning and strategic approaches to controlling dynamic uncertainty. Full article
(This article belongs to the Special Issue Dynamic Decision Making in Controlled Experiments)
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Article
Simulating Transport and Land Use Interdependencies for Strategic Urban Planning—An Agent Based Modelling Approach
Systems 2015, 3(4), 177-210; https://doi.org/10.3390/systems3040177 - 01 Oct 2015
Cited by 16 | Viewed by 4080
Abstract
Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterise urban systems. In this paper, we report on an agent based [...] Read more.
Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterise urban systems. In this paper, we report on an agent based model, called TransMob, which explicitly simulates the mutual dynamics between demographic evolution, transport demands, housing needs and the eventual change in the average satisfaction of the residents of an urban area. The ability to reproduce such dynamics is a unique feature that has not been found in many of the like agent based models in the literature. TransMob, is constituted by six major modules: synthetic population, perceived liveability, travel diary assignment, traffic micro-simulator, residential location choice, and travel mode choice. TransMob is used to simulate the dynamics of a metropolitan area in South East of Sydney, Australia, in 2006 and 2011, with demographic evolution. The results are favourably compared against survey data for the area in 2011, therefore validating the capability of TransMob to reproduce the observed complexity of an urban area. We also report on the application of TransMob to simulate various hypothetical scenarios of urban planning policies. We conclude with discussions on current limitations of TransMob, which serve as suggestions for future developments. Full article
(This article belongs to the Special Issue Agent-Based Modelling of City Systems)
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Article
Effects of Structural Transparency in System Dynamics Simulators on Performance and Understanding
Systems 2015, 3(4), 152-176; https://doi.org/10.3390/systems3040152 - 01 Oct 2015
Cited by 6 | Viewed by 3080
Abstract
Prior exploration is an instructional strategy that has improved performance and understanding in system-dynamics-based simulators, but only to a limited degree. This study investigates whether model transparency, that is, showing users the internal structure of models, can extend the prior exploration strategy and [...] Read more.
Prior exploration is an instructional strategy that has improved performance and understanding in system-dynamics-based simulators, but only to a limited degree. This study investigates whether model transparency, that is, showing users the internal structure of models, can extend the prior exploration strategy and improve learning even more. In an experimental study, participants in a web-based simulation learned about and managed a small developing nation. All participants were provided the prior exploration strategy but only half received prior exploration embedded in a structure-behavior diagram intended to make the underlying model’s structure more transparent. Participants provided with the more transparent strategy demonstrated better understanding of the underlying model. Their performance, however, was the equivalent to those in the less transparent condition. Combined with previous studies, our results suggest that while prior exploration is a beneficial strategy for both performance and understanding, making the model structure transparent with structure-behavior diagrams is more limited in its effect. Full article
(This article belongs to the Special Issue Dynamic Decision Making in Controlled Experiments)
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