Fuzzy Evaluation of the Production Strategies, Policies and Methods: Evidence from a Longitudinal Case Study

• Autorzy: Pesic Aleksandar , Pesic Duska , Ivkovic Slavko

Identyfikatory

DOI

10.24425/mper.2024.149988

• Języki publikacji: EN

Abstrakty

EN

This paper presents a model for evaluating production strategies, policies and methods based on fuzzy set theory. To illustrate the application of a model, the longitudinal case study was carried out in the sector of automotive components and parts production in Serbia. Within the automotive supplier industry, analysis is concentrated on the Cooper Standard company, one of the world’s most prominent component suppliers. The study was conducted with the management team of the Cooper Standard branch in Serbia. Triangular fuzzy numbers are employed to effectively evaluate the critical areas of production management and overall competitiveness over time. The findings of the empirical survey confirmed the usability and usefulness of the proposed approach. Also, the longitudinal character of this case study provided an opportunity to follow the patterns of change over a period of 5 years (2019–2024).

Słowa kluczowe

EN

fuzzy sets; fuzzy triangular numbers; production management; automotive suppliers

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2024
• Tom: Vol. 15, No. 1
• Strony: 35--43
• Opis fizyczny: Bibliogr. 22 poz., tab., wykr.

Twórcy

autor

Pesic Aleksandar

• MB University, Department of Business Management Faculty of Business and Law, Belgrade, Serbia

autor

Pesic Duska

• Department of Business Informatics, Vocational College of Education and Business Informatics – Sirmium, Sremska Mitrovica, Serbia, Serbia

autor

Ivkovic Slavko

• Depatrment of Management, Union-Nikola Tesla University, Faculty of Management, Serbia, Serbia

Bibliografia

• Alves Ferreira, R., A.S. Santos, L., & Esposto, KF. (2022). Quantitative supply chain segmentation model for dynamic alignment. International Journal of Production Management and Engineering, 10(2), 99–113. DOI: 10.4995/ijpme.2022.16494.
• Bourne, M., Franco-Santos, M., Micheli, P., & Pavlov, A. (2018). Performance measurement and management: A system of systems perspective. International Journal of Production Research, 56(8), 2788–2799. DOI: 10.1080/00207543.2017.1404159.
• Bustince, H., overlinerenechea, E., Pagola, M., Fernandez, J., Xu, Z., Bedregal, B., Montero, J., Hagras, H., Herrera, F., & De Baets, B. (2016). A historical account of types of fuzzy sets and their relationshipsIEEE Transactions on Fuzzy Systems, 24(1), 179–194. http://bit.ly/254KSCa.
• Dubois, D., & Prade, H. (2005). Interval-valued Fuzzy Sets, Possibility Theory and Imprecise Probability. EUSFLAT, 314–319.
• Gerocs, T., & Pinkasz, A. (2019). Relocation, Standardization and Vertical Specialization: Core–Periphery Relations in the European Automotive Value Chain. Society and Economy, 41(2), 171–192. DOI: 10.1556/ 204.2019.001.
• Gracia, M., & Paz, M.J. (2017). Network position, export patterns and competitiveness: evidence from the European automotive industry. Competition and Change, 21(2), 132–158. DOI: 10.1177/1024529417692331.
• Grodzicki, M.J., & Skrzypek, J. (2020). Cost competitiveness and structural change in value chains – verticallyintegrated analysis of the European automotive sector. Structural Change and Economic Dynamics, 55, 276–287. DOI: 10.1016/j.strueco.2020.08.009.
• Jenster, P.V., & Hussey, D. (2001). Company analysis: Determining strategic capability. Chichester, UK: John Wiley & Sons Ltd.
• Jurgens, U., & Krzywdzinski, M. (2009). Changing EastWest Division of Labour in the European Automotive Indusrtry. European Urban and Regional Studies, 16(1), 27–42. DOI: 10.1177/0969776408098931.
• Kahraman, C., & Yavuz, M. (2010). Production Engineering and Management Under Fuzziness. SpringerVerlag Berlin Heidelberg. DOI: 10.1007/978-3-642- 12052-7.
• Krzywdzinski, M. (2014). How the EU’s Eastern Enlargement Changed the German Productive Model: The Case of the Automotive Industry. Revue de La Régulation, 15(1), 1–20. DOI: 10.4000/regulation.10663.
• Lim, L.L., Alpan, G., & Penz, B. (2014). Reconciling sales and operations management with distant suppliers in the automotive industry: A simulation approach. International Journal of Production Economics,151, 20–36. DOI: 10.1016/j.ijpe.2014.01.011.
• Manello, A., & Calabrese, G. (2019). The influence of reputation on supplier selection: An empirical study of the European automotive industry. Journal of Purchasing and Supply Management, 25(1), 69–77. DOI: 10.1016/j.pursup.2018.03.001.
• Marek-Kolodziej, K., & Lapunka, I. (2020). Project prioritizing in a manufacturing-service enterprise with application of the fuzzy logic. Management and Production Engineering Review, 11(4), 81–91. DOI: 10.24425/mper.2020.136122.
• Pavlinek, P., & Zenka, J. (2011). Upgrading in the automotive industry: Firm-level evidence from Central Europe. Journal of Economic Geography, 11(3), 559–586. DOI: 10.1093/jeg/lbq023.
• Pavlinek, P. (2020). Restructuring and internationalization of the European automotive industry. Journal of Economic Geography, 20(2), 509–541. DOI: 10.1093/jeg/lby070.
• Pourabdollah, A., Mendel, J.M., & John, R.I. (2020). Alpha-cut representation used for defuzzification in rule-based systems, Fuzzy Sets and Systems, 399, 110–132. DOI: 10.1016/j.fss.2020.05.008.
• Ragin, C. (2008). Fuzzy sets: Calibration versus measurement. The Oxford Handbook of Political Methodology, Box-Steffensmeier, J.M., Brady, H.E., and Collier, D. (eds), Oxford University Press. 174–198.
• Rodriguez, R.M., Martinez, L., Torra, V., Xu, Z.S., & Herrera, F. (2014). Hesitant Fuzzy Sets: State of the Art and Future Directions. International Journal of Intelligent Systems, 29(6), 495–524. DOI: 10.1002/int.21654.
• Sturgeon, T., Memedovic, O., Van Biesebroeck J., & Gereffi G. (2009). Globalisation of the automotive industry: main features and trends. International Journal of Technological Learning, Innovation and Development, 2(1), 7–24. DOI: 10.1504/IJTLID.2009.021954.
• Wu, M.C., & Chen, T.Y. (2011). The ELECTRE multicriteria analysis approach based on Atanassov’s intuitionistic fuzzy sets. Expert Systems with Applications, 38, 12318–12327. DOI: 10.1016/j.eswa.2011.04.010.
• Zadeh, L.A. (2015). Fuzzy logic – a personal perspective. Fuzzy Sets and Systems, 281, 4–20. DOI: 10.1016/ j.fss.2015.05.009.