Suchergebnisse

Als Erstes werden die Begriffe Familiendynamik und Gruppendynamik eruiert. Es folgen sozialwissenschaftliche Überlegungen zum Verhältnis der sozialen Gebilde Familie und Gruppe. Gruppendynamik und Familientherapie als Verfahren werden dann als Teil einer Gruppenbewegung beschrieben, die ab den 1920er Jahren entstanden ist. In einem nächsten Schritt werden einige personelle, theoretische und praktische Gemeinsamkeiten der genannten multipersonellen Verfahren beschrieben. Abschließend werden Unterschiede zwischen Gruppendynamik und systemischen Verfahren vor dem Hintergrund allgemeiner Entwicklungen im psychosozialen Bereich beschrieben.

This research was conducted to determine the influence of oil price, stocks and exchange rates in Indonesia. The data used in this research is secondary data in the form of time series data stretching from November 2014 to November 2022. The Quantitative research method, which is VAR (Vector Autoregressive) was used to test and analyze hypotheses with measurable data to obtain parameters from the variables' influence. The study's results found that oil prices significantly influenced Indonesia's stock prices decline. Oil on the exchange rate was also significant, meaning last month's oil prices affected the exchange rate this month, and there was a depreciation. Still, the exchange rate was not significant for stock prices.

Status among peers has been one of the central themes of peer relations research for decades. While the topic has been extensively researched in the Western European and North American literature, less is known about such dynamics in 'non-Western' contexts. The paper intends to address this gap by analyzing the status dynamics related to the two most frequently investigated dimensions of status – popularity and acceptance – in a Hungarian, ethnically diverse, longitudinal primary school database. Additionally, we apply a novel multilevel regression model, the within-between random effects model (Bell et al., 2019), which combines the strengths of fixed- and random-effects models and makes the decomposition of within-individual and between-individual effects possible. The paper analyses the first four waves of the panel dataset (N of observations = 4441, N of individuals = 1313). Most of our results are in line with the Western European literature, highlighting the important role of being good at sports, verbal aggression, being considered smart, and physical appearance. With regard to ethnic differences, our results show ethnicized patterns in the relationship between aggression and popularity.

AbstractResearchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g. people) aggregated in stock variables. Yet many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g. body weight). This paper presents a new method to connect the micro‐level dynamics associated with elements in a population with the macro‐level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of body mass index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual‐based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual‐based model. Copyright © 2014 System Dynamics Society

AbstractStochastic aspects of systems have generally been ignored in most system dynamics studies except for purposes of sensitivity testing. Yet any model that claims to be more than simply a phenomenological description of a system must treat the underlying stochasticity explicitly in terms of its contribution to the dynamics. Recent work in chemical, biological, and hydrodynamic systems has shown that the aggregation of stochastic effects can lead to novel behavior (self‐organization in dissipative systems).In this paper, an analogy between models of these physical systems and system dynamics models is developed, in which dynamic models are seen to be an approximation (to lowest order in an expansion in system size) to a stochastic model for the system. The theoretical results derived for the physical system models are evaluated for their application to system dynamics models. A research strategy to elaborate this approach to analyzing a more general class of systems is proposed.