Logistics Performances of Gulf Cooperation Council’s Countries in Global Supply Chains
Regional integration into the Gulf Cooperation Council has enabled respective countries to effectively participate in global supply chains. To ensure effective integration of this region into global supply chains, logistics operations are a very important determinant. The aim of this study was to assess logistical performances of GCC countries, and to identify which country has the best conditions for establishing a regional logistic center. For this study, we used relevant data from Logistics Performance Index (LPI) developed by the World Bank. The research was conducted using a hybrid multicriteria approach based on the CRITIC and MABAC methods. The findings of this study indicate that the United Arab Emirates has the best conditions for establishing a regional logistics center. This study also releveled the areas of logistics in which other GCC countries should make an improvement to improve their logistical performance.
Akkermans, H., Bogerd, P., & Vos, B. (1999). Virtuous and vicious cycles on the road towards international supply chain management. International Journal of Operations & Production Management. DOI: https://doi.org/10.1108/01443579910260883
Biswas, S., & Anand, O. P. (2020). Logistics Competitiveness Index-Based Comparison of BRICS and G7 Countries: An Integrated PSI-PIV Approach. IUP Journal of Supply Chain Management, 17(2), 32-57.
Božanić, D., Tešić, D., & Kočić, J. (2019). Multi-criteria FUCOM – Fuzzy MABAC model for the selection of location for construction of single-span bailey bridge. Decision Making: Applications in Management and Engineering, 2(1), 132-146.
Božanić, D.I., Pamučar, D.S., & Karović, S.M. (2016). Application the mabac method in support of decision-making on the use of force in a defensive operation. Tehnika, 71(1), 129-136. DOI: https://doi.org/10.5937/tehnika1601129B
Chow, G., Heaver, T. D., & Henriksson, L. E. (1994). Logistics performance, International journal of physical distribution & logistics management. DOI: https://doi.org/10.1108/09600039410055981
Christopher, M. I. (2017). Logistics & supply chain management. Fourth Edition, Prentice Hall
Coe, N., Hess, M., Yeung, H., Dicken, P. & Henderson, J. (2004). Globalizing regional development: a global production networks perspective. Transactions of the Institute of British Geographers, 29(4), 468-484. DOI: https://doi.org/10.1111/j.0020-2754.2004.00142.x
Dadush, U., & Falcao, L. (2009). Regional arrangements in the Arabian Gulf. Universitäts-und Landesbibliothek Sachsen-Anhalt.
Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. DOI: https://doi.org/10.1016/0305-0548(94)00059-H
Durugbo, C. M., Amoudi, O., Al-Balushi, Z., & Anouze, A. L. (2020). Wisdom from Arabian networks: a review and theory of regional supply chain management. Production Planning & Control, 1-17.
Elevli, B. (2014). Logistics freight center locations decision by using Fuzzy-PROMETHEE. Transport, 29(4), 412-418. DOI: https://doi.org/10.3846/16484142.2014.983966
Fernandes, C., & Rodrigues, G. (2009). Dubai's potential as an integrated logistics hub. Journal of Applied Business Research (JABR), 25(3).
Ibrahim, H. W., Zailani, S., & Tan, K. C. (2015). A content analysis of global supply chain research. Benchmarking: An International Journal.
Kazançoğlu, Y., Özbiltekin, M., & Özkan-Özen, Y. D. (2019). Sustainability benchmarking for logistics center location decision. Management of Environmental Quality: An International Journal.
Khassenova-Kaliyeva, A. B., Nurlanova, N. K., & Myrzakhmetova, A. M. (2017). Central Asia as a transcontinental transport bridge based on the transport and logistic system of the countries of this region. International Journal of Economic Research, 14(7), 365-382.
Kishore, P., & Padmanabhan, G. (2016). An integrated approach of fuzzy AHP and fuzzy TOPSIS to select logistics service provider. Journal for Manufacturing Science and Production, 16(1), 51-59. DOI: https://doi.org/10.1515/jmsp-2015-0017
Klassen. R. D. & Whybark, D. C. (1994), ``Barriers to the management of international operations'', Journal of Operations Management, Vol. 11, pp. 385-96. DOI: https://doi.org/10.1016/S0272-6963(97)90006-1
Kuo, M.S. (2011). Optimal location selection for an international distribution center by using a new hybrid method. Expert Systems with Applications, 38(6), 7208-7221. DOI: https://doi.org/10.1016/j.eswa.2010.12.002
Larson, P. D., & Halldorsson, A. (2004). Logistics versus supply chain management: an international survey. International Journal of Logistics: Research and Applications, 7(1), 17-31 DOI: https://doi.org/10.1080/13675560310001619240
Li, Y., Liu, X., & Chen, Y. (2011). Selection of logistics center location using Axiomatic Fuzzy Set and TOPSIS methodology in logistics management. Expert Systems with Applications, 38(6), 7901-7908. DOI: https://doi.org/10.1016/j.eswa.2010.12.161
Martí, L., Martín, J. C., & Puertas, R. (2017). A DEA-logistics performance index. Journal of applied economics, 20(1), 169-192. DOI: https://doi.org/10.1016/S1514-0326(17)30008-9
Meijboom, B.R. & Vos, B. (1997). International manufacturing and location decisions: balancing configuration and co-ordination. International Journal of Operations & Production Management, 17(7), 790-805. DOI: https://doi.org/10.1108/01443579710175565
Memedovic, O., Ojala, L., Rodrigue, J. P., & Naula, T. (2008). Fuelling the global value chains: what role for logistics capabilities? International Journal of Technological Learning, Innovation and Development, 1(3), 353-374. DOI: https://doi.org/10.1504/IJTLID.2008.019978
Onden, I., Acar, A. Z. & Eldemir, F. (2016). Evaluation of the logistics center location using a multi-criteria spatial approach. Transport, 33(2), 322-334 DOI: https://doi.org/10.3846/16484142.2016.1186113
Ou, C. W., & Chou, S. Y. (2009). International distribution center selection from a foreign market perspective using a weighted fuzzy factor rating system. Expert Systems with Applications, 36(2), 1773-1782 DOI: https://doi.org/10.1016/j.eswa.2007.12.007
Pamučar D., & Ćirović G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016-3028. DOI: https://doi.org/10.1016/j.eswa.2014.11.057
Pham, T. Y., Ma, H. M., & Yeo, G. T. (2017). Application of Fuzzy Delphi TOPSIS to locate logistics centers in Vietnam: The Logisticians’ perspective. The Asian Journal of Shipping and Logistics, 33(4), 211-219. DOI: https://doi.org/10.1016/j.ajsl.2017.12.004
Puška, A., Beganović, A., & Šadić, S. (2018). Model for investment decision making by applying the multi-criteria analysis method. Serbian Journal of Management, 13(1), 7-28.
Puška, A., Stojanović, I., Maksimović, A., & Osmanović, N. (2020). Evaluation software of project management used measurement of alternatives and ranking according to compromise solution (MARCOS) method. Operational Research in Engineering Sciences: Theory and Applications, 3(1), 89-102.
Rao, C., Goh, M., Zhao, Y. & Zheng, J. (2015). Location selection of city logistics centers under sustainability. Transportation Research Part D: Transport and Environment, 36, 29-44. DOI: https://doi.org/10.1016/j.trd.2015.02.008
Reyes, P., Raisinghani, M. S., & Singh, M. (2002). Global supply chain management in the telecommunications industry: The role of information technology in integration of supply chain entities. Journal of Global Information Technology Management, 5(2), 48-67. DOI: https://doi.org/10.1080/1097198X.2002.10856325
Scully, J., & Fawcett, S. E. (1993). Comparative logistics and production costs for global manufacturing strategy. International Journal of Operations & Production Management, 13(12), 62-78. DOI: https://doi.org/10.1108/01443579310048191
Stević, Ž., Vesković, S., Vasiljević, M., & Tepić, G. (2015). The selection of the logistics center location using AHP method. In 2nd Logistics International Conference, 86-91.
Sun, Y., Lu, Y., & Zhang, C. (2019). Fuzzy Linear Programming Models for a Green Logistics Center Location and Allocation Problem under Mixed Uncertainties Based on Different Carbon Dioxide Emission Reduction Methods. Sustainability, 11(22), 6448.
Sundarakani, B., Tan, A. W. K., & Over, D. V. (2012). Enhancing the supply chain management performance using information technology: some evidence from UAE companies. International Journal of Logistics Systems and Management, 11(3), 306-324. DOI: https://doi.org/10.1504/IJLSM.2012.045916
Uyanik, C., Tuzkaya, G., & Oğuztimur, S. (2018). A literature survey on logistics centers' location selection problem. Sigma: Journal of Engineering & Natural Sciences/Mühendislik ve Fen Bilimleri Dergisi, 36(1), 141-160.
Wang, B., Xiong, H., & Jiang, C. (2014). A multicriteria decision making approach based on fuzzy theory and credibility mechanism for logistics center location selection. The Scientific World Journal, 2014, Article ID 347619 DOI: https://doi.org/10.1155/2014/347619
Wang, M. H., Lee, H. S., & Chu, C. W. (2010). Evaluation of logistic distribution center selection using the fuzzy MCDM approach. International Journal of Innovative Computing, Information and Control, 6(12), 5785-5796.
Zaralı, F., & Yazgan, H. R. (2016). Solution of logistics center selection problem using the axiomatic design method. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, 10(3), 547-553.
Zavadskas, E.K., Stević, Ž., Turskis, Z., & Tomašević M., (2019). A Novel Extended EDAS in Minkowski Space (EDAS-M) Method for Evaluating Autonomous Vehicles. Studies in Informatics and Control, 28(3), 255-264.
Ziadah, R. (2018). Constructing a logistics space: Perspectives from the Gulf Cooperation Council. Environment and Planning D: Society and Space, 36(4), 666-682. DOI: https://doi.org/10.1177/0263775817742916