Randomness, Emergence and Causation: A Historical Perspective of Simulation in the Social Sciences

This chapter is a review of some simulation models, with special reference to social sciences. Three critical aspects are identified--i.e. randomness, emergence and causation--that may help understand the evolution and the main characteristics of these simulation models. Several examples illustrate the concepts of the paper.

Nonparametric moment-based estimation of simulated models via regularized regression

International conference

On the quest for defining organisational plasticity: a community modelling experiment

Purpose – This viewpoint article is concerned with an attempt to advance organisational plasticity (OP) modelling concepts by using a novel community modelling framework (PhiloLab) from the social simulation community to drive the process of idea generation. In addition, the authors want to feed back their experience with PhiloLab as they believe that this way of idea generation could also be of interest to the wider evidence-based human resource management (EBHRM) community. Design/methodology/approach – The authors used some workshop sessions to brainstorm new conceptual ideas in a structured and efficient way with a multidisciplinary group of 14 (mainly academic) participants using PhiloLab. This is a tool from the social simulation community, which stimulates and formally supports discussions about philosophical questions of future societal models by means of developing conceptual agent-based simulation models. This was followed by an analysis of the qualitative data gathered during the PhiloLab sessions, feeding into the definition of a set of primary axioms of a plastic organisation. Findings – The PhiloLab experiment helped with defining a set of primary axioms of a plastic organisation, which are presented in this viewpoint article. The results indicated that the problem was rather complex, but it also showed good potential for an agent-based simulation model to tackle some of the key issues related to OP. The experiment also showed that PhiloLab was very useful in terms of knowledge and idea gathering. Originality/value – Through information gathering and open debates on how to create an agent-based simulation model of a plastic organisation, the authors could identify some of the characteristics of OP and start structuring some of the parameters for a computational simulation. With the outcome of the PhiloLab experiment, the authors are paving the way towards future exploratory computational simulation studies of OP.

A complex adaptive approach to the gender pay gap

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Model calibration and validation via confidence sets

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The increasing importance of biological sciences for creating value added in many economic sectors contributed to the rise of the now popular term “bioeconomy,” referring to “the set of economic activities relating to the invention, development, production and use of biological products and processes” (OECD, 2009), which are characterized by the accent on the reduction of environmental pollution and the adoption of sustainable practices.

Inference for Simulation Models

Still to be written

Spot the differences! The Simulated Minimum-Distance Method

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A minimum-distance estimator for the calibration of simulation models

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Emergence and Causation in Simulation Models in Social Sciences

Guest lecture