Article ID: | iaor201524850 |
Volume: | 31 |
Issue: | 2 |
Start Page Number: | 236 |
End Page Number: | 257 |
Publication Date: | Mar 2014 |
Journal: | Systems Research and Behavioral Science |
Authors: | Azadeh Ali, Teimoury Ebrahim, Darivandi Shoushtari Kosar, Saberi Mortezza |
Keywords: | systems, neural networks, artificial intelligence, economics |
Organizational cybernetics is one of the powerful systems approaches that benefits from the viable system model (VSM). The model is very general and is usually in need of complementary methods. In this article, one of artificial intelligence methods, artificial neural networks (ANNs), and system dynamics simulation have been used in support of the VSM. Iran broiler industry is conceived as a complex economic system and has been modelled using VSM. Operational elements, coordination, control, development, policy functions and environment of the industry are identified. ANN has been utilized in service of the controller (system 3) and the intelligence function (system 4) of the industry. ANN helps system 3 to anticipate market deviation from defined targets and reduce action delays for feeding the system back. A model in which ANN and system dynamics simulation are combined helps systems 4 and 5 manage external relationships by facilitation of defining imports tariff for maize and soybean, which are detected as critical environmental elements in identifying the industry environment. Maize and soybean cost contribute to more than 60% of chicken meat cost in Iran. Chicken meat is a high‐consumed product all over the world and one of the main sources of protein. Suitable price of chicken meat is an important factor for the industry managers in Iran. As illustrated in the paper, artificial intelligence can improve VSM subsystems functioning and enhance the industry intelligence and regulation against internal and external oscillations.