Case Study on Environmental Scanning

Abstract

Policy/decision makers need to an intelligent, robust, and more confidence mechanism to help them to analysis the futures impacts and overcome the future high uncertainty and complexity. Also, all environmental scanning and analysis methods in literature conduct for the current /short-term to help policy/decision makers in strategic decisions process. The core idea of our research paper is to develop an intelligent environmental scanning approach (IESA) to generate more justifiable estimation for long-term strategic view. In addition, our IESA supports policy/decision makers to reduce the future uncertainty and stimulates the domain experts to identify the major futures drivers of a specific domain. This support deals with providing new levels of awareness situation that may lead to more efficient and effective decision making process. Moreover, our IESA enhances and integrates RT-Delphi, Ontology KB, Explanation, PESTEEL, SWOT, and Structural analysis methods to generate large-scale participatory approach to help policy/decision makers for long-term environmental scanning. Final, this paper builds on our research to support policy/decision makers in the Egyptian ministry of agriculture (MOA) for developing the strategic plan (2014-2035) of the Wheat crop production.

Keywords: Intelligent Environmental scanning, Long-term view, RT-Delphi, MICMAC, SWOT, PESTEEL, Explanation, Wildcards, Egyptian Wheat production.

Source: Ahmed Mohamed Omran and Motaz Khorshid, https://core.ac.uk/download/pdf/82508895.pdf
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