A framework for model integration and holistic modelling of socio-technical systems

Wu, Paul P., Fookes, Clinton B., Pitchforth, Jegar, & Mengersen, Kerrie (2015) A framework for model integration and holistic modelling of socio-technical systems. Decision Support Systems, 71, pp. 14-27.

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This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour.

The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained.

Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.

Impact and interest:

3 citations in Scopus
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2 citations in Web of Science®

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ID Code: 79986
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Socio-Technical Systems (STS), modelling, Agent Based Model, Bayesian Network, Business Process Modelling Notation
DOI: 10.1016/j.dss.2015.01.006
ISSN: 0167-9236
Divisions: Current > Research Centres > ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS)
Current > Schools > School of Electrical Engineering & Computer Science
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Elsevier BV
Copyright Statement: This is the author’s version of a work that was accepted for publication in Decision Support Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Decision Support Systems, [VOL 71, ISSUE#, (2015)] DOI: 10.1016/j.dss.2015.01.006
Deposited On: 13 Jan 2015 02:30
Last Modified: 01 Sep 2016 01:47

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