A knowledge-based approach for Trend Impact Analysis

Policy/decision makers in governments, corporations and institutions all need to anticipate the future, analysis its impacts and be confidence about the consensus results. Future studies methods are often made to utilize quantitative and qualitative approaches using various methods such as Trend Impact Analysis (TIA). This paper introduces advanced knowledge-based trend impact analysis that integrates the enhanced Trend Impact Analysis, Structural Analysis, Ontology-based Real-Time Delphi and Explanation knowledge-based models to support the policy/decision makers with the impacts of wildcards on the future revenues and provide him to be more confident about the consensus results. This advanced knowledge-based Trend Impact analysis takes into account the benefits of knowledge sharing and explanation capabilities for generating the futures scenarios. The inputs of new TIA matrices are based on the knowledge of nominated and weighted large scale futurists and experts. The main contribution of this paper is the developed idea enhances the participatory approach for traditional TIA and overcomes different challenges of efficiency and effectiveness in the knowledge acquisition process. Also, this idea of knowledge-based TIA is novel, its implementation as a web-based tool and applied it to help policy/decision makers, in the Egyptian ministry of agriculture, for addressing the futures of the national food security.