ONE OF THE WAYS TO IDENTIFY THE WEIGHTS OF INDICATORS OF THE FUZZY ANALYTICAL HIERARCHY PROCESS FOR DETERMINING BSC OF AN AIRLINE COMPANY

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Transport Problems

Silesian University of Technology

Subject: Economics, Transportation, Transportation Science & Technology

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VOLUME 16 , ISSUE 4 (December 2021) > List of articles

ONE OF THE WAYS TO IDENTIFY THE WEIGHTS OF INDICATORS OF THE FUZZY ANALYTICAL HIERARCHY PROCESS FOR DETERMINING BSC OF AN AIRLINE COMPANY

Dinara SATYBALDIYEVA / Gulmira MUKHANOVA * / Kassym YELEMESSOV / Dinara BASKANBAYEVA / Oraz SATYBALDIYEV

Keywords : balanced scorecard; perspective; indicators; analytical hierarchy process; fuzzy analytical hierarchy process

Citation Information : Transport Problems. Volume 16, Issue 4, Pages 83-94, DOI: https://doi.org/10.21307/tp-2021-062

License : (CC BY 4.0)

Received Date : 01-June-2020 / Accepted: 05-December-2021 / Published Online: 24-December-2021

ARTICLE

ABSTRACT

This article presents the justification for the relevance of the method for assessing the performance of an airline company. Based on a survey of foreign sources, it was proposed to use the integrated method of the analytic hierarchy process using the example of “Air Astana”. The results of the method are described based on the determination of effective indicators. The conclusions are arrived at on the expediency of applying the fuzzy analytic hierarchy process (FAHP) approach for the evaluation the airline's performance. The priority (importance) and weight of all perspectives and the corresponding indicators are determined according to the proposed method. A method of assessing the probability degree of fuzzy numbers is applied to calculate the weights of the indicators (perspectives). The results of the study show that the company will be able to monitor the effectiveness of its activities using selected indicators for each perspective. The application of the instruments enhances the effectiveness of management activities of the airline and confirms the relevance of a follow-up study of the problem. This approach can be used for the management of companies in different sectors of the national economy to enhance the efficiency of management decision-making.

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1. Сатыбалдиева, Д.О. & Муханова, Г.С. & Нурмухамбетова, З.C. Əуекомпания үшін көрсекіштердің теңдестірілген жүйесін жасау. Қазақстан Республикасы Ұлттық инженерлiк академиясының ХАБАРШЫСЫ. Алматы 2018. No 2 (68). No 2 (68). P. 125-131. [In Kazakh: Satybaldiyeva, D. & Mukhanova, G. & Nurmukhambetova Z. Development of a Balanced Scorecard for the airline. Bulletin of the National Academy of Engineering of the Republic of Kazakhstan].

2. Kaplan, R. & Norton, D. Using the Balanced Scorecard as a strategic management system. Harvard Business Review. Managing for the long term. 2007. Р. 1-15.

3. AirAstana JSC. The annual report 2018. Available at: http://www.airastana.com.

4. The introduction of a balanced scorecard. Horvath & Partners. Translation from German - Moscow: Alpina Business Books. 3-ed. 2008. 478 p.

5. Kaplan, R. & Norton, D. Translating Strategy Into action. The balanced scorecard. Harvard Business School Press. 1996. 336 p.

6. Ольве, Н.-Г. & Рой, Ж. & Веттер, М. Оценка эффективности деятельности компании. Изд-во «Вильямс». 2003. 304 p. [In Russian: Olve, N.-G. & Roy, J. & Vetter, M. Assessment of the effectiveness of the company. Publishing House "Williams"].

7. Tseng, M.-L. Implementation and performance evaluation using the fuzzy network balanced scorecard. Computers & Education. 2010. Vol. 55. No. 1. Р.188-201.

8. Al Frijat, Y.S. Activating Balanced Scorecard importance as a way to improve the accounting education in Jordanian Universities. International Business Research. 2018. Vol. 11. No. 9. Р. 66- 78.

9. Staš, D. & Lenort, R. & Wicher, P. & Holman, D. Green transport Balanced Scorecard model with analytic network process support. Sustainability. 2015. Vol. 7. P. 15243-15261.

10. Nnamseh, M.P. & Umoh, V.A. Efficacy of Balanced Scorecard on performance of Banks in Nigeria. European Journal of Business and Management. 2019. Vol. 11. No. 23. Р. 33-40.

11. Shivakumar, U. & Ravi, V. & Venkateswaran, T.R. Quantification of Balanced Scorecard using crisp and fuzzy multi attribute decision making: application to banking. In: Emerging Trends in Engineering and Technology. 6th International Conference (ICETET). 2013. Р. 164-170.

12. Kairu, E.W. & Wafula, M.O. & Okaka, O. & Odera, O. & Akerele, E.K. Effects of Balanced Scorecard on performance of firms in the service sector. European Journal of Business and Management. 2013. Vol. 5. No. 9. Р. 81-88.

13. Ibrahim, M. & Murtala, S. The relevance of Balanced Scorecard as a technique for assessing performance in the Nigerian banking industry. European Journal of Business, Economics and Accountancy. 2015. Vol. 3. No. 4. Р. 71-80.

14. Owusu, A. Business intelligence systems and bank performance in Ghana: The Balanced Scorecard approach. Cogent Business and Management. 2017. No. 4(1364056). Р. 1-22.

15. Shaverdi, M. & Akbari, M. & Tafti, S.F. Combining fuzzy MCDM with BSC approach in performance evaluation of Iranian private banking sector. Advances in Fuzzy Systems. 2011. Vol. 2011. Article ID 148712. Р. 1-12.

16. Nanayakkara, G. & Iselin, E.R. An exploratory study of the performance of microfinancing institutions using the Balanced Scorecard approach. International Journal of Business and Information. 2012. Vol. 7. No. 2. Р. 165-204.

17. Nurcahyo, R. & Pustiwari, S. & Sihono Gabriel, D. Developing a strategy map based on sustainability balanced scorecard framework for manufacturing industry in Indonesia. International Journal of Engineering and Technology. 2018. Vol. 7. No. 2.34. Р. 48-51.

18. Madleňák, R. & Madleňáková, L. Multi-criteria evaluation of E-shop methods of delivery from the customer’s perspectives. Transport Problems. 2020. Vol. 15. No. 1. P. 5-14.

19. Говорова, П.С. Особенности формирования коммерческой стратегии авиакомпании. Проблемы современной экономики. 2010. № 2-3. С. 209-213. [In Russian: Govorova, P.S. Features of the formation of the commercial strategy of the airline. Problems of the modern economy. 2010. Nos. 2-3. Р. 209-213].

20. Петрашин, В.Д. Управление производительностью в авиакомпании на примере ПАО «Аэрофлот – Российские Авиалинии». Московский экономический журнал. 2019. № 9. С. 659- 672. [In Russian: Petrashin, V.D. Production management of the airline on the example of PAO "Aeroflot" - Russian Airlines. Moscow Economic Journal. 2019. No. 9. P. 659-672].

21. Saaty, T.L. The analytic hierarchy process. New York: McGraw- Hill. 1980. 296 p.

22. Caninéo, J.L.C. & Klen, T. & Reitz, G.S. & Bouzon, M. A fuzzy AHP approach for evaluating reverse logistics indicators in Brazil. In: 24th International Conference on Production Research. 2017. Р. 702-707.

23. Srichetta, P. & Thurachon, W. Applying fuzzy analytic hierarchy process to evaluate and select product of notebook computers. International Journal of Modeling and Optimization. 2012. Vol. 2. No. 2. Р. 168-173. Thailand.

24. Shaldarbekov, K. & Mukhanova, G. et al. 2018. Regional projects selection based on multi-criteria evaluation. Journal of Advanced Research in Law and Economics. 2018. Vol. IX. No. 6(36). P. 2026-2034.

25. Тутыгин, А.Г. & Коробов, В.Б. Преимущества и недостатки метода анализа иерархий. Известия РГПУ им. А.И. Герцена. Естественные и точные науки. 2010. No. 122. P. 108-115. [In Russian: Tutygin, A.G. & Korobov, V.B. Advantages and disadvantages of the method of analysis of hierarchies. Bulletin of the Russian Pedagogical University. A.I. Herzen. Natural and exact sciences].

26. Buckley, J.J. Fuzzy hierarchical analysis. Fuzzy sets and systems. 1985. Vol. 17. No. 3. Р. 233-247.

27. Yang, C.-C. & Chen, B.-S. Key quality performance evaluation using Fuzzy AHP. Journal of the Chinese Institute of Industrial Engineers. 2004. Vol. 21. No. 6. Р. 543-550.

28. Chen, C.T. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems. 2000. Vol. 114. No. 1. Р. 1-9.

29. Леоненков, А.В. Нечеткое моделирование в среде MATLAB и fuzzyTECH. Изд-во БХВПетербург. 2003. 736 p. [In Russian: Leonenkov, A.V. Fuzzy modeling in MATLAB and fuzzy TECH. BHV – Petersburg].

30. Chang, D.-Y. Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research. 1996. Vol. 95. No. 3. P. 649-655.

31. Mahendran, P. & Moorthy, M.B.K. & Saravanan, S. Fuzzy AHP approach for selection of measuring instrument for engineering college selection. Applied Mathematical Sciences. 2014. Vol. 8. No. 44. Р. 2149-2161.

32. Satybaldiyeva, D. & Mukhanova, G. & Satybaldiyev, O. & Dossova, S. & Shaldarbekova, K. Determination of effective balanced indicators in the airline company using a modified Fuzzy Analytical Hierarchy Process approach. Journal of Advanced Research in Low and Economics. Fall 2018. Vol. IX. No. 8(38). P. 2798-2810.

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