Developing a new multidimensional model for selecting strategic plans in balanced scorecard
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AbstractThe main motivation of this research is to develop an innovative multidimensional model through multi attribute decision making (MADM) methods for strategic plans selection process in the Balanced Scorecard (BSC). The current study has adopted MADM analytical methods including AHP, ELECTRE, BORDA, TOPSIS and SAW to rank the initiatives / strategic plans in BSC. Then the results of those methods have been compared against each other in order to find a robust model for selecting strategic plans. The correlation coefficient between methods has indicated that multidimensional and ELECTRE methods with 0.944 are the best and AHP with negative correlation (–0.455) is the worst method for selecting strategic plans in BSC. It has shown that the model can be useful and effective tool to finding the critical aspects of evaluation criteria as well as the gaps to improve company’s performance for achieving desired level. Developing multidimensional model is the core model for the selection of strategic plans. This study addresses the problem and issues of group decision making process for selecting strategic plans in BSC. It has numerous contributions that particularly includes; 1) Determination of the explicit criteria sub-criteria and criteria to improve ranking strategic plans in BSC, 2) Adopting MADM analytical methods including AHP, ELECTRE, BORDA, TOPSIS and SAW for the selection of strategic plans decision problem in BSC, 3) Developing multidimensional model to address the selection of strategic plans problems in BSC. The proposed model will provide an approach to facilitate strategic plans decision problem in BSC.
CitationDaniel, J. and Merigó, J.M., (2020). 'Developing a new multidimensional model for selecting strategic plans in balanced scorecard'. Journal of Intelligent & Fuzzy Systems, (Preprint), pp. 1-10.
JournalJournal of Intelligent & Fuzzy Systems