In various stages of a modeling study, the developer/user encounters the need for identifi cation of specifi c values for certain model parameters. However, due to the non-linear nature of these models it is generally hard to foresee changes in the dynamic behavior as a consequence of even marginal parameter changes. Thus, the need for an automated and effi cient search approach is very clear. A behavior pattern-based parameter search approach and results obtained from various test experiments are presented in this paper. The pattern identifi cation algorithm used enables a parameter search process based on qualitative features of a desired behavior pattern, even in the absence of a reference data series. The approach conducts the search process so as to obtain values for the model parameters that yield an output that matches the desired behavior in terms of its qualitative pattern features. Experiments conducted reveal the viability of the approach as a support tool that can be used in model calibration, sensitivity analysis, validation, and policy design stages.
The purpose of this study is to find out under what conditions homophily reinforce the diffusions over social networks or undermines them. To realize this aim, formal modeling approach is utilized and an Agent-Based Model is constructed. Afterwards, diffusion of a non-sticky innovation is investigated with the experiments having varying homophily levels in a social network with two distinct kinds of agents as the primary control variable. The results show that (i) homophily reinforces itself (ii) looking at the macrobehavior of the diffusion, initial increases in the level of homophily has a positive effect on adopted fraction of the population whereas further increases have a negative impact, and (iii) looking at the micro-behavior of the diffusion, increasing homophily can result in local maxima even the macro trend is decreasing. Connectedness and average degrees interacting with social persuasion are the two explanatory remarks in the course of investigating the impact of homophily. As a by-product, the model is also capable of capturing the segregation dynamics over social networks. Future research involves allowing the adopted innovation to lead to value homophily, exploration of the different diffusion initiation types and adoption heuristics.
Despite high degrees of uncertainty associated with graphical functions, sensitivity analysis of these functions has received less attention than parametric sensitivity analysis. Recently, a promising method was proposed in the literature to generate alternative functional forms, reducing the problem to that of parametric sensitivity. Yet the usability of the method for graphical functions in system dynamics has not been investigated. We apply this function distortion method to a sample model and identify a number of shortcomings, such as a limited variety of alternative forms. We then propose extensions to the method to address the shortcomings, and subsequently test the extensions. We find the (extended) method of function distortion to be readily applicable and efficient in testing the sensitivity of model outputs to variations in the form of graphical functions. The proposed extensions increase the variety of possible distortions, but further research can be conducted on the control of the distortions.
Abstract:In this article, we take stock of the findings from conceptual and empirical work on the role of transition initiatives for accelerating transitions as input for modeling acceleration dynamics. We applied the qualitative modeling approach of causal loop diagrams to capture the dynamics of a single transition initiative evolving within its regional context. In doing so, we aim to address two key challenges in transition modeling, namely conceptualization, and the framing of empirical insights obtained for various case study regions in a consistent modeling framework. Our results show that through this systematic approach one can translate conceptual and qualitative empirical work into a transition model design. Moreover, the causal loop diagrams can be used as discussion tools to support dialogue among researchers and stakeholders, and may support a comparison of transition dynamics across case-study regions. We reflect on main limitations related to empirical model validation (lack of data) and to model structure (high level of aggregation), and describe next steps for moving from a qualitative single transition initiative to a quantitative multiple transition initiatives model.
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