[Biomedical-cybernetics] CFP : Advanced Modeling Methods for Organizational Dynamics

[Guastello, Stephen]

Call for Papers:
Special Issue of Nonlinear Dynamics, Psychology, and Life Sciences on
Advanced Modeling Methods for Organizational Dynamics

NDPLS is actively searching for manuscripts for a special issue to be entitled, “Advanced Modeling Methods for Organizational Dynamics.” OVERVIEW: Standard methods of investigation currently applied in Organizational Psychology do not guarantee the possibility of analyzing and predicting outcomes of the macroscopic structure, as well as the emergent properties of complex systems such as business organizations. New research methods have come to the foreground, however, starting from some solid scientific studies on individual behavior and using advanced computing techniques capable of “growing up" phenomena at the macro level, making it possible to obtain counterintuitive findings about behavior and implications in organizations. The new computational approaches additionally permit one to experiment with parameters such as individual rationality, something that is difficult to address with a purely statistical approach. With these issues in mind, the present call for paper aims to collect a series of contributions in organizational studies that are not purely simulation based, but a hybrid between the classical statistical modeling approach, and nonlinear dynamic modeling. Potential papers should feature the merits of a particular computational technique and how it provides new insights into organizational dynamics. Applications to industry, other work organizations, or supply chains, at the individual, group, organizational, or project level of analysis are all welcome.

The purview of the journal is critical to the inclusion of articles: Nonlinear Dynamics, Psychology, and Life Sciences publishes papers that augment the fundamental ways we understand, describe, model, and predict nonlinear phenomena in psychology and the life and social sciences. One or more of the following nonlinear concepts must be an explicit part of the exposition: attractors, bifurcations, chaos, fractals, solitons, catastrophes, self-organizing processes, cellular automata, genetic algorithms and related evolutionary processes, neural networks, and agent-based models. The broad mixture of the disciplines represented here indicates that many bodies of knowledge share common principles. By juxtaposing developments in different fields within the life and social sciences, the scientific communities may obtain fresh perspectives on those common principles and their implications. Because the journal is multidisciplinary in scope, each article should constructed for understanding by a broad readership.

Full-text papers need to arrive for review by March 31, 2017. For further information about suggested topics, manuscript preparation and submission, please visit:www.societyforchaostheory.org/ndpls 



We look forward to your manuscripts.

Sincerely,


Riccardo Sartori, Ph.D., riccardo.sartori at univr.it and Andrea Ceschi, Ph.D., andrea.ceschi at univr.it University of Verona
Special issue editors
Stephen J. Guastello, Ph.D., stephen.guastello at marquette.edu
NDPLS Editor in Chief
Published by the Society for Chaos Theory in Psychology & Life Sciences


















 


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.ruhr-uni-bochum.de/pipermail/biomedical-cybernetics/attachments/20170221/dca53e2f/attachment-0001.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: CVbackdrop5.gif
Type: image/gif
Size: 34956 bytes
Desc: not available
URL: <http://lists.ruhr-uni-bochum.de/pipermail/biomedical-cybernetics/attachments/20170221/dca53e2f/attachment-0001.gif>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Rossler-Blue.JPG
Type: image/jpeg
Size: 10105 bytes
Desc: not available
URL: <http://lists.ruhr-uni-bochum.de/pipermail/biomedical-cybernetics/attachments/20170221/dca53e2f/attachment-0001.jpe>