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Organization Performance Composite Index Under Fuzziness: Application on Manufacturing Organization

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Measuring the organization's performance is essential for continuous improvement and operational excellence. Appropriate organizational measures include multiple dimensions. The relative importance of the multiple dimensions varies depending on the organization's context and the management team's visions. The vagueness and ambiguity in the management team's perspective toward the dimensions and associated sub-indicators show fuzzy property. This paper aims to synthesize the over-all organization performance in one aggregated index, engage the management team through index formulation, deal with ambiguity and vagueness in the management team perspective using fuzzy mathematics, and use the synthesized index in monitoring and controlling the organization's performance to achieve operational excellence. The proposed approach is implemented in manufacturing organizations to prove practicality. The implementation of the proposed method shows a positive im-pact on the organization's performance monitoring as the management team focused on one measure. Furthermore, it has engaged the management team in selecting and weighing the leading group and associated KPIs. The R programming and Minitab 19 are used in the collected data processing.
Rocznik
Strony
14--22
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
  • Faculty of statistical research and studies, Cairo University, Egypt
  • Faculty of statistical research and studies, Cairo University, Egypt
Bibliografia
  • 1. Adane, T.F., Nicolescu, M., 2018. Towards a generic framework for the performance evaluation of manufacturing strategy: An innovative approach. Journal of Manufacturing and Materials Processing, 2(2). DOI: 10.3390/jmmp2020023
  • 2. An, H.J., Kim, W.K., 2019. A case study on the influence factors of financial performance of Korean automotive parts cooperation companies through research hypothesis. Journal of Asian Finance, Economics and Business, 6(3), 327-337. DOI: 10.13106/jafeb.2019.vol6.no3.327
  • 3. Bergeron, F., Raymond, L., Rivard, S., 2004. Ideal patterns of strategic alignment and business performance. Information and Management, 41(8), 1003-1020. DOI: 10.1016/j.im.2003.10.004
  • 4. Bernardo, S.M., Rampasso, I.S., Quelhas, O.L.G., Filho, W.L., Anholon, R., 2022. Method to integrate management tools aiming organizational excellence. Production, 32. DOI: 10.1590/0103-6513.20210101
  • 5. Czerwińska, K., Pacana, A., 2022. Analysis of the maturity of process monitoring in manufacturing companies. Production Engineering Archives, 28(3), 246-251. DOI: 10.30657/pea.2022.28.30
  • 6. Eskandari, D., Jabbari Gharabagh, M.A.B., 2019. Developing a sustainability index for Mauritian manufacturing companies. Ecological Indicators, 96 (August 2018), 250-257. DOI: 10.1016/j.ecolind.2018.09.003
  • 7. Dickel, D.G., Moura, G.L. de., 2016. Organizational performance evaluation in intangible criteria: a model based on knowledge management and innovation management. RAI Revista de Administração e Inovação, 13(3), 211–220. DOI: 10.1016/j.rai.2016.06.005
  • 8. Dolge, K., Kubule, A., Blumberga, D., 2020. The composite index for energy efficiency evaluation of industrial sector: sub-sectoral comparison. Environmental and Sustainability Indicators, 8(May). DOI: 10.1016/j.indic.2020.100062
  • 9. Dubois, D., Prade, H., 1987. The mean value of a fuzzy number. Fuzzy Sets and Systems, 24(3), 279-300. DOI: 10.1016/0165-0114(87)90028-5
  • 10. Eskandari, D., Gharabagh, M.J., Barkhordari, A., Gharari, N., Panahi, D., Gholami, A., Teimori-Boghsani, G., 2021. Development of a scale for assessing the organization’s safety performance based fuzzy ANP. Journal of Loss Prevention in the Process Industries, 69(March 2020), 104342. DOI: 10.1016/j.jlp.2020.104342
  • 11. Gupta, H., Eskandari, D., Gharabagh, M. J., Barkhordari, A., Gharari, N., Panahi, D., Gholami, A., Teimori-Boghsani, G., Hosseini Ezzabadi, J., Dehghani Saryazdi, M., Mostafaeipour, A., Dickel, D.G., Moura, G.L. de, Hassan, A.S., & Jaaron, A.A.M., 2021. Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS. RAI Revista de Administração e Inovação, 226(March 2020), 127366. DOI: 10.1016/j.jlp.2020.104342
  • 12. Hamann, P.M., Schiemann, F., 2021. Organizational performance as a set of four dimensions: An empirical analysis. Journal of Business Research, 127(January), 45–65. DOI: 10.1016/j.jbusres.2021.01.012
  • 13. Hassan, A.S., Jaaron, A.A.M., 2021. Total quality management for enhancing organizational performance: The mediating role of green manufacturing practices. Journal of Cleaner Production, 308(May), 127366. DOI: 10.1016/j.jclepro.2021.127366
  • 14. Hosseini Ezzabadi, J., Dehghani Saryazdi, M., Mostafaeipour, A., 2015. Implementing Fuzzy Logic and AHP into the EFQM model for performance improvement: A case study. Applied Soft Computing Journal, 36, 165–176. DOI: 10.1016/j.asoc.2015.06.051
  • 15. Kaldas, O., Shihata, L.A., Kiefer, J., 2020. An index-based sustainability assessment framework for manufacturing organizations. Procedia CIRP, 97, 235-40. DOI: 10.1016/j.procir.2020.05.231
  • 16. Krynke, M., 2021. Management optimizing the costs and duration time of the process in the production system. Production Engineering Archives, 27(3), 163-170. DOI: 10.30657/pea.2021.27.21
  • 17. Kynčlová, P., Upadhyaya, S., Nice, T., 2020. Composite index as a measure on achieving Sustainable Development Goal 9 (SDG-9) industry-related targets: The SDG-9 index. Applied Energy, 265(March). DOI: 10.1016/j.apenergy.2020.114755
  • 18. Navimipour, N.J., Milani, F.S., Hossenzadeh, M.. 2018. A model for examining the role of effective factors on the performance of organizations. Technology in Society, 55(April), 166-174. DOI: 10.1016/j.techsoc.2018.06.003
  • 19. Rajak, S., Vinodh, S., 2015. Application of fuzzy logic for social sustainability performance evaluation: A case study of an Indian automotive component manufacturing organization. Journal of Cleaner Production, 108, 1184-1192. DOI: 10.1016/j.jclepro.2015.05.070
  • 20. Richardson, G.L., 2020. Project Management Body of Knowledge. In Project Management Theory and Practice. DOI: 10.1201/b17589-7
  • 21. Siwiec, D., Pacana, A., 2021. Method of improve the level of product quality. Production Engineering Archives, 27(1), 1–7. DOI: 10.30657/pea.2021.27.1
  • 22. Tomov, M., Velkoska, C., 2022. Contribution of the quality costs to sustainable development. Production Engineering Archives, 28(2), 164–171. DOI: 10.30657/pea.2022.28.19
  • 23. Tudose, M.B., Rusu, V.D., Avasilcai, S., 2022. Financial performance – determinants and interdependencies between measurement indicators. Business, Management and Economics Engineering, 20(1), 119-138. DOI: 10.3846/bmee.2022.16732
  • 24. Wiedenmann, M., Größler, A., 2021. Supply Risk Exposure Measurement in Manufacturing Supply Networks: An Index Construction Approach. Procedia CIRP, 104, 289–294. DOI: 10.1016/j.procir.2021.11.049
  • 25. Zadeh, L.A., 1978. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1), 3–28.10.1016/0165-0114(78)90029-5
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f80cb184-ced1-4443-a04f-d23174994220
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