Ahmed Omran

An intelligent DSS to anticipate the impacts of wildcards on the tourism industry in Egypt

Research on the future of the Egyptian tourism industry has become the subject of countless studies and debates. Different wildcards have high impacts on this crucial industry and ultimately of the future of the Egyptian national income. This paper is about an Intelligent Decision Support System (DSS) that specifically focuses on assessing the impacts of wildcards on the future revenues of the Egyptian tourism industry. The developed DSS integrates both qualitative and quantitative DSS methods (called the enhanced Trend Impact Analysis and Real-Time Delphi Survey). Also, the developed analytical tool is used to generate various scenarios (not just a single forecast) by modifying the extrapolation of historical trends in view of tourism experts.

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.

Structural Analysis with Knowledge-based MICMAC Approach

term view, policy/decision makers need to justifiable anticipation for the major future drivers that may effect on their domain key variables. In this paper, we develop a knowledge-based structural analysis approach that based on integrating of RT-Delphi, structural analysis, knowledge- based and explanation modeling capabilities. We applied the developed approach in two crucial domains in Egypt, which are food security and water security (milk production). In addition, it was 15 and 25 experts participate in food security and water security cases. They share knowledge for identifying, analyzing and foreseeing potentials of Egypts water and food security as ground to thinking of pilot solutions aimed at evading problems and futures drivers as well as developing a repository of knowledge whereby Egypts policy/decision makers are attained.