Multifaceted Modelling of Complex Business Enterprises


Autoria(s): Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin J.; Ma, Lin; Lassen, David
Data(s)

2015

Resumo

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/91195/

Publicador

Public Library of Science

Relação

http://eprints.qut.edu.au/91195/1/fetchObject.action.pdf

DOI:10.1371/journal.pone.0134052

Chakraborty, Subrata, Mengersen, Kerrie, Fidge, Colin J., Ma, Lin, & Lassen, David (2015) Multifaceted Modelling of Complex Business Enterprises. PLoS ONE, 10(8), e0134052.

Direitos

Copyright: © 2015 Chakraborty et al

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Fonte

School of Chemistry, Physics & Mechanical Engineering; School of Electrical Engineering & Computer Science; School of Mathematical Sciences; Science & Engineering Faculty

Tipo

Journal Article