A primary influence vertex approach to identify driving factors in complex integrated agri-industrial systems – an example from sugarcane supply and processing systems
提出一种基于因果网络分析的主要影响顶点方法，用于识别和排序驱动综合农业工业系统性能的关键因素，并在南非四个甘蔗加工厂验证了方法的有效性。
Integrated agri-industrial systems (IAISs), such as sugarcane supply and processing systems, are complex systems and hence generally difficult to understand and manage. The large number factors in IAISs coupled with the complex interrelationships among the factors make it challenging to identify the points of intervention for improving their overall performance. Several approaches, such as the network theory and the Theory of Constraints have been used to identify important factors in systems with variations in success. This paper demonstrates a primary influence vertex approach for identifying and ranking the factors that drive the performance of IAISs. The approach is based on comprehensive causal network analyses and was tested in four relatively diverse large-scale sugarcane milling operations in South Africa. Results from the analyses were found to be consistent with the literature and external knowledge of the milling areas as at the time of the study. It is concluded that the approach can proffer a sound basis from which deeper rooted problems in systems can be identified on an ongoing basis. It is, however, recommended that the approach should be systematically compared with other relevant methods that are used to analyse complex systems.