<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

Management Systems in Production Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

This paper aims to rank strategic objectives in a strategy map to improve the efficiency of strategy implementation. Objectives are ranked based on strategic...

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

Online veröffentlicht: 28. Aug. 2019

Seitenbereich: 153 - 161

Eingereicht: 01. Jan. 2019

Akzeptiert: 01. Mai 2019

DOI: https://doi.org/10.1515/mspe-2019-0025

Schlüsselwörter
Balanced Scorecard (BSC), Logarithmic Fuzzy Preference Programming (LFPP), similarity method, Strategy map

© 2019 Hossein Safari et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Online veröffentlicht: 28. Aug. 2019

Seitenbereich: 153 - 161

Eingereicht: 01. Jan. 2019

Akzeptiert: 01. Mai 2019

DOI: https://doi.org/10.1515/mspe-2019-0025

SchlüsselwörterBalanced Scorecard (BSC), Logarithmic Fuzzy Preference Programming (LFPP), similarity method, Strategy map

© 2019 Hossein Safari et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Balanced Scorecard (BSC), Logarithmic Fuzzy Preference Programming (LFPP), similarity method, Strategy map