Dynamics Of Socio-economic Systems Research Articles

Development of a behaviour pattern-based testing approach for coupled socioeconomic and environmental models

Understanding the interactions between human and environmental systems is key to sustainable environmental management. Dynamically Coupled Socioeconomic system dynamics models integrated with physically-based Environmental Models (DCSEMs) are promising tools to appropriately capture the non-linear relationships between complex socioeconomic and biophysical systems, thereby supporting sustainable environmental management. However, existing approaches for testing integrated models are commonly based on the point-to-point analysis of model outputs, which is not suitable for DCSEMs that are behaviour pattern oriented. Consequently, the lack of well-defined behaviour pattern-based approaches has limited the adaptability of DCSEMs. To address this gap, this study proposes a novel behaviour pattern-based model testing approach that includes global sensitivity analysis (GSA), auto-calibration algorithms, and evaluation to assess behaviour pattern similarities between model outputs and real-world trends. The proposed approach is demonstrated through a real-world case study, in which an existing DCSEM is calibrated and evaluated to simulate water table depth in the Rechna Doab region of Pakistan. Compared to the conventional numerical point approach, the proposed approach is better suited for DCSEMs, as it replicates observed system behaviour patterns (as opposed to observed point values) over time. Furthermore, the outcomes of the Theil inequality statistical analysis and parameter distribution analysis provide evidence that the suggested approach is effective in testing and improving the performance of the DCSEM by capturing the spatial heterogeneity within the study area. The proposed behaviour-pattern testing procedure is a useful approach for model testing in data-limited, spatially-distributed DCSEMs.

Special issue on dynamics of socioeconomic systems: systemic risk—complex systems

Special issue on dynamics of socioeconomic systems: systemic risk—complex systems

Special issue on dynamics of socioeconomic systems: systemic risk—finance

Over the past decades, complexity has emerged as an alternative way to understand and model complex dynamical phenomena in a number of fields. Instead of focusing on local and independent behaviors, complexity suggests that observed phenomena are the results of complex interactions between components of a system. The DySES conference, which took place at the Sorbonne in 2018, gave the unique opportunity to present the state of the art in the complexity field and in many areas including the socioeconomic ones. This special issue of Soft Computing presents papers in finance both in the field of complexity and beyond it. Many topics are covered. Jay et al. focus on portfolio management and introduce robust covariance matrices using recent developments in the random matrix theory (RMT). Levantesi et al. propose a novel approach, combining the random forest and the 2D P-spline in order to provide a more accurate mortality rate forecasting, therefore extending the Lee–Carter model. Chorro et al. focus on option pricing. They start from the inverse Gaussian GARCH model and build a new pricing kernel. Cerqueti et al. work on complex networks and introduce new influence measures based on vertex centrality. They apply their measure to the SP100 universe. Still within the complexity field, Gatfaoui et al. introduce a test of non-chaoticity when data are noisy. They show that financial data do not have a chaotic behavior. Fiori et al. build a model to capture systemic risk. In particular, they set the focus on the inequalities of wealth and income, using the well-known Gini coefficient. Di Paolo tackles the problem of the increase in life expectancy with regard to pension funds and annuity providers. The concept of observed survival probabilities is extensively used. Within a related area, D’Amato et al. propose a de-risking strategy model for LTC insurers that face demographic changes implying disability risks. They suggest new methodologies. Baione et al. consider non-life risk premium and study the diversification effect. They use quantile regressions to estimate the individual conditional loss. Kaucic et al. study investment strategies known as enhanced indexing. They introduce an improved version of the particle swarm optimization algorithm (PSO) and present an example using the Euro Stoxx. At last, Kudlak et al. question the importance of dedicated local budgets concerning crisis management. As guest editors, we would like to thank Soft Computing for giving us the opportunity to have this special issue done on all these topics.

Development of a behaviour-pattern based global sensitivity analysis procedure for coupled socioeconomic and environmental models

Dynamically Coupled Socioeconomic system dynamics models integrated with physically-based Environmental Models (DCSEM) can capture relationships between complex environmental and socioeconomic systems, and are promising tools for participatory environmental management involving the integration of various viewpoints, disciplines and processes for sustainable water resources management. However, the application of DCSEMs has been limited for many reasons, including the complexity of the model coupling process (i.e., the lack of a flexible model coupling approach), issues of over-parameterization, high parameter uncertainty, intensive computational requirements (due to many interacting parameters), and the possibility of eliciting behaviour-pattern oriented model outputs. As such, most conventional (numerical) procedures for model evaluation (i.e., analysis of point values of modelled results) that have been implemented for physically-based models are not applicable to DCSEMs. In order to address these challenges, this study developed a novel automatic behaviour-pattern global sensitivity analysis (GSA) procedure to determine the influence of input parameters on the general behaviour trends (rather than numerical point values) of coupled model outputs. The developed behaviour-pattern GSA procedure was implemented in an existing software (Tinamït), developed previously by the authors, to ensure ease-of-use. This study investigates the suitability of the proposed behaviour-pattern GSA procedure for the analysis of DCSEMs by comparing the proposed procedure with the conventional numerical procedure. The numerical and proposed behaviour-pattern procedures, coupled with the Morris (qualitative) and EFAST (quantitative) GSA methods, were applied to a DCSEM to rank and screen parameters in a water table depth simulation in Pakistan. The determination of important parameters facilitates subsequent model calibration and groundwater management. It was found that the Morris and EFAST methods achieved similar parameter ranking results in the numerical and behavioural procedures, respectively. The results also indicated that the behaviour-pattern GSA procedure offers more information about several important parameters, and a variety of parameter ranking orders, compared to the numerical GSA procedure, regardless of which GSA method (Morris or EFAST) was used. The increased information obtained through the application of the developed behaviour-pattern procedure confirms that the DCSEM model outputs are behaviour-oriented. It is recommended that the proposed behaviour-pattern GSA procedure be used with the Morris method, which has a higher computational efficiency (>150 times) than the EFAST method, to detect important parameters in DCSEMs.

Stra.Tech.Man (Strategy-Technology-Management): Theory and Concepts

This volume presents some fundamental elements to the Stra.Tech.Man approach, which the author of this book tried to develop during the last few years. The main challenge of the Stra.Tech.Man approach is to synthesize interpretatively the analytical spheres of strategy, technology, and management, upon the effort of any socioeconomic organization to innovate, survive, and develop. The following chapters search to define and apply in particular the multiple applications of the Stra.Tech.Man concept. They use this approach as an analytical mechanism to perceive in the context of the current transformative phase of globalization the aspects of competitiveness, innovation, and change management. This volume includes the following chapters that apply the aspects of the Stra.Tech.Man analysis: I. The Greek firms into globalization: The Stra.Tech.Man approach Globalization is not a static and finished status quo: it is subject to a continuous transformation and restructuring. At the same time, globalization is not a timeless, a historical, and automatically homogenizing phenomenon. Every attempt of scientific understanding, interpretation, and prediction of the partial socioeconomic dynamics and developments is becoming increasingly infertile and disorientating, insofar as the rigid analytic division between the “national” and the “international” continues unaltered; globalization is a complex, dialectic, and evolutionary phenomenon. The study of globalization through the examination of the synthesizing and co-evolving incorporation of partial socioeconomic structures (social, economic and sectoral) and corporate subsystems in terms of strategy, technology, and management (“Stra.Tech.Man” triangle) constitutes a new approach for the study of the globalization process. II. Innovation in Stra.Tech.Man terms Contrary to the conventional neoclassical perspective, the approaches focusing on the evolutionary nature of the capitalist firm are probably more comprehensive in the study of innovation. This chapter attempts a theoretical refocusing in the analysis of innovation, by following a perspective of “biological” type. It highlights the synthesis of “strategy-technology-management” as the organic center that generates and re-generates the phenomenon of innovation within the socioeconomic organizations. III. Innovation in economics and management: The Stra.Tech.Man synthesis Economics and the theoretical analysis of entrepreneurship and organizational theory keep up with producing innovation theories with remarkably various forms and analyses. This chapter suggests that economics and management science can be “analytically bridged” if we reposition the phenomenon of innovation into the evolutionary/physiological Stra.Tech.Man “core” of the organization. In this theoretical perspective, the firm as a “living organism” operates as structural co-creator of the economic sectors and the socioeconomic systems that host its entrepreneurial activity. IV. Change management and innovation in Stra.Tech.Man terms In the current context of globalization’s restructuring, the concepts of change management and innovation are co-evolving. A counter-proposed theoretical perspective in terms of the evolutionary Stra.Tech.Man triangle is useful for the successful innovative action of all socioeconomic organizations. This chapter suggests the concept of change management in Stra.Tech.Man terms in five consecutive steps as a novel approach to the phenomenon of organizational change. V. Fostering micro and meso competitiveness in Stra.Tech.Man terms In the current restructuring phase of globalization, since all partial socioeconomic systems are inescapably entering an ever-deeper process of “organic restructuring,” the content of competitiveness is changing structurally. To this end, it seems that a repositioned developmental economic policy is necessary, which can focus on fostering the competitiveness of the locally operating entrepreneurial actors. This chapter proposes specifically the concept of competitiveness as a synthesis of the three fundamental micro, meso, and macro levels that create and reproduce the systemic competitiveness. It also presents the Stra.Tech.Man perspective on the proposal of creation of the Local Development and Innovation Institutes (LDIs) as useful dimensions to strengthen local business systems in combined terms of meso- and micro- competitiveness. In conclusion, the “Stra.Tech.Man approach” attempts to define a unifying and evolutionary field of research, by initiating its exploration on the inner “physiology” of the socioeconomic organization. This approach extends analytically from the micro to the meso- and macro- level of socioeconomic system dynamics and vice versa.

Modeling of the Parties' Vote Share Distributions

Competition between varying ideas, people and institutions fuels the dynamics of socio-economic systems. Numerous analyses of the empirical data extracted from different financial markets have established a consistent set of stylized facts describing statistical signatures of the competition in the financial markets. Having an established and consistent set of stylized facts helps to set clear goals for theoretical models to achieve. Despite similar abundance of empirical analyses in sociophysics, there is no consistent set of stylized facts describing the opinion dynamics. In this contribution we consider the parties' vote share distributions observed during the Lithuanian parliamentary elections. We show that most of the time empirical vote share distributions could be well fitted by numerous different distributions. While discussing this peculiarity we provide arguments, including a simple agent-based model, on why the beta distribution could be the best choice to fit the parties' vote share distributions.

Heterogeneidad del paisaje y diversidad de especies arbóreas en un boque tropical. Desarrollo y validación de una propuesta metodológica

Delgado L.A. 2018. Landscape Heterogeneity and tree species diversity in a tropical forest. Development and validation of a methodological proposal. Ecosistemas 27(1): 105-115. Doi.: 10.7818/ECOS.1475 Many landscapes exist as unstable spatial-temporal mosaics where changes in patterns of biodiversity are affected by nature processes and the dynamic interaction between social and ecological factors. It is a consequence of the natural dynamics of socio-economic systems that regulate man-made tropical forests. However, a significant proportion of studies have made generalizations about the relative values of biodiversity, without taking into account the high levels of internal heterogeneity in the biophysical properties and land uses of each site. The purpose of this study is to propose and validate a methodology to delimit the heterogeneity of the landscape based on criteria that integrate the coupling of human-ecological systems such as: space-time dynamics of deforestation and fragmentation; complexity of the landscape structure; current and historical land use and biophysical variability. For this, the use of satellite images, landscape metrics, field work, documentary review and multivariate analysis were combined. The proposed methodology is intended to help guide the empirical delimitation of landscape heterogeneity as a prerequisite for the selection of similar landscapes and forest patches in studies of the diversity of tree species, in order to provide an opportunity to control the possible difficulties caused by variability in the proportion of forests, landscape configuration and successional states, in estimating its effects on forest richness and floristic composition.

РАЗВИТИЕ МЕТОДОЛОГИЧЕСКИХ ОСНОВ МОДЕЛИРОВАНИЯ СОЦИАЛЬНО-ЭКОНОМИЧЕСКИХ СИСТЕМ В КОНТЕКСТЕ УПРАВЛЕНИЯ РАЗВИТИЕМ

Complexity of economic systems modeling for ef-ficiency assessment of their functioning and elabora-tion of development forecasts can be explained by a number of factors. One of them is heterogeneity of economic systems, significant dependence of their structure and principles of key elements interaction on the management level, industry membership, the scope of system work. Vector and development dynamics of socio-economic system are determined, on the one hand, by internal potential of its elements , each im-plements its own development trajectory on the micro-level, and on the other hand – by opportunities of the external environment which is characterized by a com-plex mix of macroeconomic, political, social, technolo-gical and natural factors.
 Analysis of the existing development 
 methods of economic systems models at different levels allows marking out several modeling technologies among which the most promising from the point of view of application in real management practice can be considered the technology of imitation modeling based, in turn, on three methodological approaches.
 For the solution of a modeling problem of regional socio-economic system combined approach application appears to be the most effective within which external macroprocesses are modeled by means of system dynamics, and internal – socio-economic processes are formalized by agent-based modeling methods.

Will there be a revolution in Russia in 2017?

In this paper on the base of mathematical model the tendencies, that have taken place in the socio-economic system of Russia at the end of 2013, are studied. Based on the revealed tendencies the outlook of dynamics of socio-economic system of Russia in the near future (up to 2017) is analyzed. On the base of research results it is possible to conclude that in Russia there are symptoms of a revolutionary situation at the end of 2016 and at the beginning of 2017.

An integrated system dynamics model developed for managing lake water quality at the watershed scale

A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies.

On the validity of use of physical equations and principles in the socio-economic field and on the predictability of socio-economic system dynamics

Usually, the various empirical and semi-empirical equations and mathematical models are used to study the dynamics of socio-economic systems. In this case, there are very often questions related to the validity of application of such equations and models. In this paper, it is shown that the dynamics of socio-economic systems can be described by mathematical equations analogous to the motion equations that are well known in physics (particularly in classical mechanics). In this connection, it is possible to say that the predictability of the dynamics of a socio-economic system is described by the motion equations (i.e., Newton's equations) to the same degree that these equations predict the dynamics of the physical system. Such models allow us to determine the trends of development in the dynamics of socio-economic systems. The importance of this investigation in using adequate mathematical models is that they allow us to notice those or other adverse trends in the socio-economic systems, therefore, ensuring timely optimal management decisions.

On the economic foundations of green growth discourses: the case of climate change mitigation and macroeconomic dynamics in economic modeling

‘Greening’ economic growth discourses are increasingly replacing the catchword of ‘sustainable development’ within national and international policy circles. The core of the argument is that the growth of modern economies may be sustained or even augmented, while policy intervention simultaneously ensures sustained environmental stewardship and improved social outcomes. But how well are these claims scientifically grounded or supported by economic theory, evidence, and applied modeling? We address this question with reference to the economic modeling of climate mitigation policies. We argue that orthodox economic equilibrium and optimization thinking offers, in effect, little support to and insufficiently meaningful interpretations of green growth claims. There are several exciting strands of new economic thinking that are emerging, offering a more robust and empirically validated understanding of the potential for green growth paths. Nonoptimizing simulation models are arguably in a better position to capture socioeconomic system dynamics and the role of macroeconomic policies for sustainability governance. An important caveat, nevertheless, is that when judged against the evidence, greening growth remains to some extent an oxymoron as to date there has been little evidence of substantial decoupling ofGDPfrom carbon‐intensive energy use on a wide scale. Moreover, although the rhetoric on ‘greening the economy’ actively supports the need for policy intervention, the macroeconomic reasoning behind this, remains ambiguous. We finally suggest that, although focusing on the dichotomy between growth and the environment is clearly important, the quality of growth and beyond growth dimensions are at least as important for delivering improved macroeconomic governance for sustainability.This article is categorized under:Energy and Climate > Climate and EnvironmentEnergy and Development > Economics and Policy

DIVERSITY AND ECONOMIC EVOLUTION: FAILURES OF COMPETITIVE ECONOMIC SYSTEMS

This paper has two themes. First, diversity of relevant attributes driving the dynamics of socioeconomic systems, including industrial systems'is often needed to increase their likelihood of transiting to a superior state. However, systems left to their own devices do not always evolve to states where they possess sufficient or optimal diversity for further evolution or growth to a superior state. Evolutionary market mechanisms can be of this nature. Structural adjustment policies and globalization seem to be adding to industrial and other types of uniformity. Hence, real danger exists that global industrial structures influenced by field effects will become “piled up” and reduce the likelihood of the global economic system evolving to a superior economic state. Furthermore, diversity is an important driving force in other growth processes, e.g., those adding to the stock of knowledge. Second industrial diversity of techniques and behaviors may be potentially Paretian valuable as a means of optimal adjustment to continual technological change and as a manifestation of specialization according to differences in individual abilities and in those of organizations. Insofar as attempts at benchmarking try to ensure uniform adoption of “best practice” in industry, they are likely to be doubly damaging because short‐run potential Paretian benefits are forgone, and in stifling industrial diversity they may also undermine industrial diversity as a source of future economic growth. (JEL D00, D89, O30, 014)

Limits of model-based prediction of socioeconomic system behavior

The use of mathematical and computer-implemented models for study of socioeconomic system dynamics has become increasingly popular in recent years. In their enthusiasm for these methods, many investigators have ignored, or seriously underestimated, certain intricate technical problems which place stringent limitations on the validity of model-based predictions. This article is intended to provide a brief discussion of these matters. For clarity it is perhaps best to begin with a few simple definitions.

Review of Progress in cybernetics and systems research, Vol 4: Cybernetics of cognition and learning, structure and dynamics of socio-economic systems, health care systems, engineering systems methodology.

Review of Progress in cybernetics and systems research, Vol 4: Cybernetics of cognition and learning, structure and dynamics of socio-economic systems, health care systems, engineering systems methodology.

Dynamics of Socio-Economic Systems

Automatic control engineers are the best-trained people in society for understanding the behavior of feedback loops: Feedback loop structure underlies the dynamics of social and economic behavior. Yet experts in dynamics are exerting little influence on human affairs. The responsibility lies with those having capability to use their knowledge where it can do most for the public. Probably the greatest benefit would come from working on major social issues, not from refining the operation of physical systems. At M.I.Τ. we have been developing a comprehensive simulation model as a basis for examining the forces underlying inflation, unemployment, energy shortage, foreign exchange rates, mobility of people, and tax policy. By making all variables endogenous, the feedback structure is preserved. The model is a step toward bridging from the concepts of feedback dynamics to social policy.