The aim of this paper is to explicate the concept of complex adaptive systems and identify key elements, characteristics and methods of modelling and simulation of complex adaptive systems presented by the theoretical analyses from literature. Background. The study of complex adaptive systems has yielded great insight into how complex, natural-like structure that balance on the boundary between order and chaos can evolve order and purpose over time. Supporting evidence for this proposition is based within existing industries to be involved in bonded rationality of economics, networks and management theory. Initial theoretical-oriented investigation has revealed and indicated that economy and business organizations is best analyzed from perspective of complexity science. Specific propositions regarding the nature of dynamic change in organizational development has to be explored, driven by the complex adaptive systems model. Methods. The paper details a theoretical analysis for analyzing complex adaptive systems concept and then uses it to prove to economics and business. Findings. An exploratory study of complex adaptive systems can reveal that agent based modelling and simulation, nonlinear multilevel regression, study of cellular automata and chaos in the light of complexity theory would be an alternative approach to propitiate new understanding about the nature of economy, especially, organizational development and expectations. In doing so, the complex adaptive systems approach through new quantitative and qualitative research methodology grounded in economics and management theory will set new insights and research areas for organzations. Conclusion. Complexity science builds on the rich traditions of system theory. Complex economic models would be best explored by the use of complex adaptive systems as a framework with using agent based modelling and simulation, nonlinear multilevel regression, cellular automata and chaos theory.