Tedarik Zinciri Proje Yöneticisi Seçim Probleminde Hibrit Yaklaşım

Öz

Tedarik zinciri yönetimi imalat firmalarının malzeme ihtiyaçlarının belirlenmesinden değer katılarak dönüştürülen ürünlerin müşterilere ulaştırılmasına kadar tüm süreçlerin yönetimini kapsamaktadır. Literatürde tedarik zinciri yönetim süreçlerine yönelik teorik yaklaşımlar ve pratik uygulamalar sunulmaktadır. Fakat tedarik zinciri süreçlerinin iyileştirilmesine yönelik proje tabanlı tedarik zinciri proje yönetici seçimine rastlanmamaktadır. Bu araştırmada tedarik zinciri proje yöneticisi seçim problemi ele alınmıştır. Bu kapsamda proje yöneticisi seçim problemi uygulamalarına yönelik kullanılan çok kriterli karar verme tekniklerinden faydalanılmıştır. Literatür incelemesi ve imalat firması yönetici jürisi ile yapılan görüşmelere göre yedi kriter belirlenmiştir. Kriter ağırlıkları F-SWARA yöntemiyle belirlenmiştir. Dört aday arasından en uygun adayın seçimi için OCRA-G yöntemi uygulanmıştır. Araştırma bulgularına göre tedarik zinciri proje yöneticisi seçiminde tecrübe kriteri en önemli kriter olarak belirlenmiştir. İkinci aday en uygun aday olarak bulunmuştur. Bu araştırmada bulanık ve grey tabanlı yaklaşımlar hibrit şekilde kullanılarak literatüre proje seçim problemi için alternatif hibrit model yöntemi sunulmuştur. Ayrıca imalat firmalarına, tedarik zinciri proje yönetici adaylarına, araştırmacılara öneriler geliştirilmiştir.

Anahtar Kelimeler

• Proje Yöneticisi Seçim Problemi
• İnsan Kaynakları Yönetimi
• Tedarik Zinciri Yönetimi
• F-SWARA
• OCRA-G

Hybrid Approach to Supply Chain Project Manager Selection Problem

Abstract

Supply chain management covers the management of all processes, from determining the material needs of manufacturing companies to delivering value-added products to customers. Theoretical approaches and practical applications for supply chain management processes are presented in the literature. However, there is no project-based supply chain manager selection for the improvement of supply chain processes yet. In this research, the supply chain project manager selection problem is discussed. In this context, multi criteria decision making techniques used for project manager selection problem applications were used. According to the literature review and interviews with the manufacturing executive jury, seven criteria were determined. The criterion weights were determined by the fuzzy the stepwise weight assessment ratio analysis (F-SWARA) method. The grey operational competitiveness rating method (OCRA-G) method was applied to select the most suitable candidate among the four candidates. According to the research findings, the experience criterion was determined as the most important criterion in the selection of the supply chain project manager. The second candidate was found to be the most suitable candidate. In this research, an alternative hybrid model method for the project selection problem has been presented to the literature by using fuzzy and gray based approaches in a hybrid way. In addition, suggestions have been developed for manufacturing companies, supply chain project manager candidates and researchers.

Keywords

• Project Manager Selection Problem
• Human Resource Management
• Supply Chain Management
• F-SWARA
• OCRA-G

Kaynakça

1. Afshari, A. R., Anisseh, M., Shahraki, M. R., & Hooshyar, S. (2016). PROMETHEE use in Personnel selection. In Proceedings of the International Conference on ICT Management for Global Competitiveness and Economic Growth in Emerging Economies-ICTM. http://ieomsociety.org/ieom2017/papers/56.pdf
2. Afshari, A., & Kowal, J. (2017). Decision making methods for the selection of ICT project manager. Gospodarka Rynek Edukacja= Economy Market Education, 18(4), 19-28. http://dx.doi.org/10.2139/ssrn.3118075
3. Afshari, A. R., & Yusuff, R. M. (2013). Fuzzy integral project manager selection. Australian Journal of Multi-Disciplinary Engineering, 9(2), 149-154. https://doi.org/10.7158/14488388.2013.11464855
4. Ahsan, K., Ho, M., & Khan, S. (2013). Recruiting project managers: A comparative analysis of competencies and recruitment signals from job advertisements. Project Management Journal, 44(5), 36-54. https://doi.org/10.1002/pmj.21366
5. Alimardani, M., Hashemkhani Zolfani, S., Aghdaie, M. H., & Tamošaitienė, J. (2013). A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technological and economic development of economy, 19(3), 533-548. https://doi.org/10.3846/20294913.2013.814606
6. Ansari, Z. N., Kant, R., & Shankar, R. (2020). Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. International Journal of Sustainable Engineering, 13(6), 473-494. https://doi.org/10.1080/19397038.2020.1758973
7. Chaghooshi, A., Arab, A., & Dehshiri, S. (2016). A fuzzy hybrid approach for project manager selection. Decision Science Letters, 5(3), 447-460. https://doi.org/10.5267/j.dsl.2016.1.001
8. Chen, L. S., & Cheng, C. H. (2005). Selecting IS personnel use fuzzy GDSS based on metric distance method. European journal of operational research, 160(3), 803-820. https://doi.org/10.1016/j.ejor.2003.07.003

9. Çelikbilek, Y. (2018). A grey analytic hierarchy process approach to project manager selection. Journal of Organizational Change Management, 31(3), 749-765. https://doi.org/10.1108/JOCM-04-2017-0102
10. Dağdeviren, M. (2010). A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems. Journal of Intelligent manufacturing, 21(4), 451-460. https://doi.org/10.1007/s10845-008-0200-7
11. Dodangeh, J., Sorooshian, S., & Afshari, A. R. (2014). Linguistic extension for group multicriteria project manager selection. Journal of Applied Mathematics, 2014. https://doi.org/10.1155/2014/570398
12. Heidary Dahooie, J., Beheshti Jazan Abadi, E., Vanaki, A. S., & Firoozfar, H. R. (2018). Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology. Human Factors and Ergonomics in Manufacturing & Service Industries, 28(1), 5-16. https://doi.org/10.1002/hfm.20713
13. Ijadi Maghsoodi, A., Ijadi Maghsoodi, A., Poursoltan, P., Antucheviciene, J., & Turskis, Z. (2019). Dam construction material selection by implementing the integrated SWARA—CODAS approach with target-based attributes. Archives of Civil and Mechanical Engineering, 19(4), 1194-1210. https://doi.org/10.1016/j.acme.2019.06.010
14. Jazebi, F., & Rashidi, A. (2013). An automated procedure for selecting project managers in construction firms. Journal of Civil Engineering and Management, 19(1), 97-106. https://doi.org/10.3846/13923730.2012.738707
15. Keršuliene, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of business economics and management, 11(2), 243-258. https://doi.org/10.3846/jbem.2010.12
16. Khodadadi, E., & Aghabeigi, M. (2018). A Novel Hybrid MCDM Approach Based on Fuzzy DEMATEL, ANP, and Fuzzy VIKOR for Selecting the Best Project Managers. International Journal of Information Technology Project Management (IJITPM), 9(2), 38-64. https://doi.org/10.4018/ijitpm.2018040103
17. Madić, M., Petković, D., & Radovanović, M. (2015). Selection of non-conventional machining processes using the OCRA method. Serbian Journal of Management, 10(1), 61-73. https://doi.org/10.5937/sjm10-6802
18. Manaan, O. A., Ahadzie, D. K., Panford, J. K., & Proverbs, D. G. (2014). Competency-based evaluation of project managers’ performance in mass house building projects in Ghana–the fuzzy set theory approach. Journal of Science and Technology (Ghana), 34(1), 46-62. http://dx.doi.org/10.4314/just.v34i1.5
19. Mavi, R. K., Goh, M., & Zarbakhshnia, N. (2017). Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry. The International Journal of Advanced Manufacturing Technology, 91(5), 2401-2418. https://doi.org/10.1007/s00170-016-9880-x
20. Mishra, A. R., Rani, P., Pandey, K., Mardani, A., Streimikis, J., Streimikiene, D., & Alrasheedi, M. (2020). Novel multi-criteria intuitionistic fuzzy SWARA–COPRAS approach for sustainability evaluation of the bioenergy production process. Sustainability, 12(10), 4155. https://doi.org/10.3390/su12104155
21. Parkan, C. (1994). Operational competitiveness ratings of production units. Managerial and Decision Economics, 15(3), 201-221. https://doi.org/10.1002/mde.4090150303
22. Rashidi, A., Jazebi, F., & Brilakis, I. (2011). Neurofuzzy genetic system for selection of construction project managers. Journal of Construction Engineering and Management, 137(1), 17-29. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000200
23. Sadatrasool, M., Bozorgi-Amiri, A., & Yousefi-Babadi, A. (2016). Project manager selection based on project manager competency model: PCA–MCDM Approach. Journal of Project Management, 1(1), 7-20. https://doi.org/10.5267/j.jpm.2017.1.004
24. Stanujkic, D., Zavadskas, E. K., Liu, S., Karabasevic, D., & Popovic, G. (2017). Improved OCRA method based on the use of interval grey numbers. Journal of Grey System, 29(4), 49-60.
25. Torfi, F., & Rashidi, A. (2011). Selection of project managers in construction Firms using analytic hierarchy process (AHP) and fuzzy Topsis: a case study. Journal of Construction in Developing Countries, 16(1), 69-89. http://eprints.usm.my/42162/1/JCDC_16_1_ART_4__69-89_.pdf
26. Toygar, A., Yildirim, U., & İnegöl, G. M. (2022). Investigation of empty container shortage based on SWARA-ARAS methods in the COVID-19 era. European Transport Research Review, 14(1), 1-17. https://doi.org/10.1186/s12544-022-00531-8
27. Ulutaş, A., Popovic, G., Stanujkic, D., Karabasevic, D., Zavadskas, E. K., & Turskis, Z. (2020). A new hybrid MCDM model for personnel selection based on a novel grey PIPRECIA and grey OCRA methods. Mathematics, 8(10), 1698. https://doi.org/10.3390/math8101698
28. Varajão, J., & Cruz-Cunha, M. M. (2013). Using AHP and the IPMA Competence Baseline in the project managers selection process. International Journal of Production Research, 51(11), 3342-3354. https://doi.org/10.1080/00207543.2013.774473
29. Wu, H. H. (2002). A comparative study of using grey relational analysis in multiple attribute decision making problems. Quality Engineering, 15(2), 209-217. https://doi.org/10.1081/QEN-120015853
30. Xing, B., & Zhang, A. D. (2006). Application of fuzzy analytical hierarchy process in selecting a project manager. In 2006 International Conference on Management Science and Engineering (pp. 1417-1421). IEEE. https://doi.org/10.1109/ICMSE.2006.314252
31. Zarbakhshnia, N., Soleimani, H., & Ghaderi, H. (2018). Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria. Applied Soft Computing, 65, 307-319. https://doi.org/10.1016/j.asoc.2018.01.023
32. Zavadskas, E. K., Turskis, Z., Tamošaitiene, J., & Marina, V. (2008). Multicriteria selection of project managers by applying grey criteria. Technological and economic development of economy, 14(4), 462-477. https://doi.org/10.3846/1392-8619.2008.14.462-477
33. Zavadskas, E. K., Vainiūnas, P., Turskis, Z., & Tamošaitienė, J. (2012). Multiple criteria decision support system for assessment of projects managers in construction. International journal of information technology & decision making, 11(02), 501-520. https://doi.org/10.1142/S0219622012400135
34. Zhang, S. F., & Liu, S. Y. (2011). A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Systems with Applications, 38(9), 11401-11405. https://doi.org/10.1016/j.eswa.2011.03.012
35. Zhao, L., Guo, Y., & Cui, W. (2009). The application of fuzzy comprehensive evaluation methods in the selection of a project manager. In 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology (pp. 1387-1391). IEEE. https://doi.org/10.1109/ICCIT.2009.233