Ranking strategic objectives in a strategy map based on Logarithmic Fuzzy Preference Programming and similarity method

• Autorzy: Safari Hossein , Khanmohammadi Ehsan , Maleki Meysam , Cruz-Machado Virgilio , Shevtshenko Eduard

Identyfikatory

DOI

10.1515/mspe-2019-0025

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

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

• Wydawca: STE GROUP
• Czasopismo: Management Systems in Production Engineering
• Rocznik: 2019
• Tom: nr 3 (27)
• Strony: 153--161
• Opis fizyczny: Bibliogr. 40 poz., rys., tab.

Twórcy

autor

Safari Hossein

• University of Tehran, Faculty of Management Nasr Bridge, North Kargar St. 6311-14155, Tehran, Iran

autor

Khanmohammadi Ehsan

• University of Tehran, Faculty of Management Nasr Bridge, North Kargar St. 6311-14155, Tehran, Iran

autor

Maleki Meysam

• Universidade Nova de Lisboa, UNIDEMI Department of Mechanical and Industrial Engineering, Portugal

autor

Cruz-Machado Virgilio

• Universidade Nova de Lisboa, UNIDEMI R&D in Mechanical and Industrial Engineering, Portugal

autor

Shevtshenko Eduard

• Tallinn University of Technology (TalTech) Department of Mechanical and Industrial Engineering, Estonia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).