Ranking Strategic Objectives in a Strategy Map Based on Logarithmic Fuzzy Preference Programming and Similarity Method

Abstract

This paper aims to rank strategic objectives in a strategy map to improve the efficiency of strategy implementation. Objectives are ranked based on strategic destinations using the combination of Logarithmic Fuzzy Preference Programming (LFPP) and similarity method. In the first step, the weight of strategic destinations is obtained using LFPP technique; then objectives are ranked by similarity method. Similarity method uses the concept of alternative gradient and magnitude for effectively solving the general multi-criteria analysis problem. Finally, objectives are ranked in an actual strategy map. As a practical and efficient tool, the proposed approach can assist managers and decision-makers in drawing more efficient output from strategy maps.

Keywords

• balanced scorecard (bsc)
• logarithmic fuzzy preference programming (lfpp)
• similarity method
• strategy map