Modeling Of Socio-economic Systems Research Articles

The Dynamics of Coalition Formation on Complex Networks

Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

The Irrationality Illusion: A New Paradigm for Economics and Behavioral Economics

A new conceptual and formal framework for analyzing economic decisions, the homo communitatis paradigm, is introduced. The framework is in the form of seven principles, which collectively articulate the entire range of factors that affect choice, including all aspects of individual behavior and of the social context—the communities—the actor is a member of. Traditional economic analysis is shown to be a special case of homo communitatis analysis in which key variables are omitted. Using the principles, we show that experimental results such as loss aversion, framing effects, mental accounting, and judgment biases are not irrational and that the apparent irrationality is in every case an illusion arising from incomplete specification and control of independent variables elucidated in the principles. Several implications for future work are discussed, including high-fidelity models of socioeconomic systems, significantly more powerful and detailed economics simulations, and adoption of significantly different approach to design of economic experiments, one that takes into account all the variables involved in human choice.

Socioeconomic modelling using the DEVS formalism

This paper deals with a new approach to the modelling of socioeconomic systems. In these models, there are many interacting entities (agents, players). The whole market comes up as a result of these interactions. In terms of the economy, this concept is based on the Subject-Need-Good triad. The subject in this model represents an economical subject with needs that can be satisfied by the consumption of a good. In terms of computational modelling, this concept is based on the Discrete Event System Specification (DEVS) formalism, where each subject is represented by one coupled DEVS. This coupled DEVS contains several atomic DEVS. There are only three types of atomic DEVS – generator/store, transformer and optimiser. The basic process of the concept is the transformation that changes one type of a good to another or uses a good to satisfy a need. This experimental frame will be used for the design and development of a new dynamic approach based on dynamic Petri nets.

Cognitive Approach to Modeling Reflexive Control in Socio-Economic Systems

Traditional approaches to support of decision making do not consider system dynamics of processes and the individual characteristics of the actors (subjects). Considering this, the theory of reflexive control has gained wide acceptance and application. Another approach to modeling socio-economic systems is cognitive modeling. It, however, does not account for reflexivity. Therefore, this article describes a new approach that tries to combine the strengths of the two approaches to modeling of socio-economic systems.

Socioeconomic Aspects of the Gabčíkovo Hydropower Plant

An approach of space structures graphic modelling has been applied in the study of the Gabčíkovo Hydropower Plant (GHP) effects on its hinterland. The model of socioeconomic system of the Gabčíkovo hinterland served as a base. Changes in the socioeconomic systems in the hinterland linked with the construction and operation of the GHP and effects that would be caused by the demolition of the reservoir were examined on the model.

Modelling of Large-Scale Socio-Economic Systems and Policies

The paper deals with a model of socio-economic system, which is composed of demographic, household, employment and economic subsystems. The model includes also the socio-economic policy unit, responsible for wages, social services such as education, health service, social security, social care etc., which determine the standard of living of the population. As a result of that policy the specific labour participation, Which depends on family size and type of household follows. The paper concentrates first of all, on the household and employment submodels. To evaluate the model parameters the polish statistical data has been used. The model can be used for planning of the soc io-economic development.

The econometric challenge to system dynamics and vice versa: Some future perspectives

In the last years, there have been some attempts to compare different approaches for dynamic modeling of socioeconomic systems and to suggest guidelines for choosing among them. This paper continues these efforts with special emphasis on system dynamics and econometrics, which are commonly regarded as the roughest competitors in this field of simulation. It will present a detailed catalogue of model features, relevant for an adequate characterization of system dynamics and econometrics, and will stress the importance to notice the interconnections that exist between different features. The paper then gives a systematic survey of the conceivable relations between system dynamics and econometrics, and closes with a short epistemological outlook.

Causality: Its characterization in system dynamics and KSIM models of socioeconomic systems

Two methodologies—Kane's KSIM and Forrester's system dynamics—for modeling socioeconomic systems are compared and contrasted with regard to the manner in which each characterizes and classifies casuality in socioeconomic systems. The equivalence of the so-called casual diagram used in system dynamics to the cross-impact matrix used in KSIM is indicated. Each method identifies exactly two classes of casual links—the similarity between the classes distinguished in system dynamics with those employed in KSIM is suggested. Then the assumptions regarding the nature of causality that are implicit within the two methodologies are compared. In this context techniques for translating linear system-dynamics models to KSIM-like models (and vice versa) are provided. Examples are provided to illustrate the notions discussed in the article.

Contributors To This Issue

Contributors To This Issue

Mathematical Models of Socio-Economic Systems: An Example

This paper uses a specific example of a relatively simple socio-economic system to demonstrate a methodology for developing state models of socio-economic systems in terms of the structural features of the system. Numerical values of the parameters in the resulting model are either determined from past records of the organization or are obtainable from surveys. A computer solution is presented to indicate the general nature of the performance characteristics that can be simulated with such a model.