Grey Strategies Interaction Model
Purpose - This paper aims to implement the strategies selection process in a proposed formulated mathematical framework to prioritize selected strategies with the interaction of other groups of strategies, known as the strategies interaction model (SIM). Design/methodology/approach - SWOT analysis is a popular useful strategic planning tool, which analyzes organizations internal and external factors. The traditional SWOT procedure lists internal and external factors and derives four groups of strategies based on the organization’s strategic position. SWOT is easy to use as a business analyzing tool, while it is not competent enough for strategic formulation. With the emergence of the economy's vicissitudes, undulations in the markets and multiple changes, and various variables in the industrial competitive environment, selection of the organization strategies confront uncertainty in decision-making. The SIM framework presents a solution to select alternative strategies for organizations in unpredictable situations. Findings – The findings show that SIM is a reliable approach to evaluate, select and rank organization’ strategies. SIM proposes alternative strategies due to the uncertainty of the organization’ environment with respect to the four strategic positions. The SIM’ proposed ranking process is in accordance with the highest impact of each strategy on each other. Furthermore, it possesses advantages of AHP, ANP and other applied MCDM techniques in SWOT analysis. Practical implications - In this paper SIM is applied within a dairy company located in the north of Iran. Originality/value - SIM has the advantages of the classic SWOT and fills the gaps of MCDM methods application in the SWOT analysis. Moreover, it provides a formulated algorithm for the organizations to face the uncertainty of the environment. SIM philosophy can be widely used in the decision and managerial implications.
Citation:Zakeri, S., Yang, Y. and Hashemi, M. (2018) Grey Strategies Interaction Model. Journal of Strategy and Management, 12 (1), pp. 30-60
Research Group:Institute of Artificial Intelligence (IAI)