Evaluation of the logistics center locations using a multi-criteria spatial approach
Abstract
The private sector assumes that logistics centers create cost benefits for their operations. On the other hand, the public sector also assumes that logistics sectors maintain harmony with an aim to improve the logistics network structure and efficiency. In Turkey, nineteen logistics centers are on-going to develop a system approach and integrate different transportation modes to increase logistics performance. In this study, we focused on a multi-stage methodology that combines the fuzzy analytic hierarchy process, spatial statistics and analysis approaches to evaluate the suitability degrees of the logistics centers in the study area. To reach the suitability levels, seven decision criteria were considered alongside their priority levels. These criteria were proximities to highway, railway, airports, and seaports; volume of international trade; total population; and handling capabilities of the ports. The reached suitability degrees were tested using a sensitivity analysis. Different scenarios were discussed to understand how the decision environment might illustrate differences in spatial aspect.
First published online 25 May 2016
Keyword : suitability analysis, logistics center, sustainable logistics management, geographic information systems (GIS), fuzzy analytic hierarchy process (F-AHP)
How to Cite
Önden, I., Acar, A. Z., & Eldemir, F. (2018). Evaluation of the logistics center locations using a multi-criteria spatial approach. Transport, 33(2), 322–334. https://doi.org/10.3846/16484142.2016.1186113
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Maister, D. H. 1976. Centralisation of inventories and the “square root law”, International Journal of Physical Distribution 6(3): 124–134. http://doi.org/10.1108/eb014366
McCoy, J.; Johnston, K.; Kopp, S.; Borup, B.; Willison, J. 2004. ArcGIS 9: Using ArcGIS Spatial Analyst. 4th edition. ESRI Press. 233 p.
McKinnon, A. 2009. The present and future land requirements of logistical activities, Land Use Policy 26(1): S293–S301. http://doi.org/10.1016/j.landusepol.2009.08.014
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Onden, I.; Tuzla, H.; Cobb, S. 2012. Evaluation of retail store location alternatives for investment decisions using the Delphi technique and geographic information systems, International Business: Research, Teaching and Practice 6(2): 64–75.
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Uçal Sarı, I.; Öztayşi, B.; Kahraman, C. 2013. Fuzzy analytic hierarchy process using type-2 fuzzy sets: an application to warehouse location selection, in M. Doumpos, E. Grigoroudis (Eds.). Multicriteria Decision Aid and Artificial Intelligence: Links, Theory and Applications, 285–308. http://doi.org/10.1002/9781118522516.ch12
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Wang, Y.-M.; Luo, Y.; Hua, Z. 2008. On the extent analysis method for fuzzy AHP and its applications, European Journal of Operational Research 186(2): 735–747. http://doi.org/10.1016/j.ejor.2007.01.050
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Ashrafzadeh, M.; Rafiei, F. M.; Isfahani, N. M.; Zare, Z. 2012. Application of fuzzy TOPSIS method for the selection of warehouse location: a case study, Interdisciplinary Journal of Contemporary Research in Business 3(9): 655–671.
Bozdağ, C. E.; Kahraman, C.; Ruan, D. 2003. Fuzzy group decision making for selection among computer integrated manufacturing systems, Computers in Industry 51(1): 13–29. http://doi.org/10.1016/S0166-3615(03)00029-0
Buckley, J. J. 1985. Fuzzy hierarchical analysis, Fuzzy Sets and Systems 17(3): 233–247. http://doi.org/10.1016/0165-0114(85)90090-9
Chang, D.-Y. 1996. Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research 95(3): 649–655. http://doi.org/10.1016/0377-2217(95)00300-2
Christopher, M. 2016. Logistics & Supply Chain Management. 5th edition. FT Press. 328 p.
Cuomo, A. 2008. Development Profile for Warehouse/Distribution/Logistics Center Sites. 11 p. Available from Internet: http://www.esd.ny.gov/BusinessPrograms/Data/BuildNow/BNNY_Warehouse-Profile-082608.pdf
Dablanc, L. 2007. Goods transport in large European cities: difficult to organize, difficult to modernize, Transportation Research Part A: Policy and Practice 41(3): 280–285. http://doi.org/10.1016/j.tra.2006.05.005
Delgado, M. G.; Sendra, J. B. 2004. Sensitivity analysis in multicriteria spatial decision-making: a review, Human and Ecological Risk Assessment: An International Journal 10(6): 1173–1187. http://doi.org/10.1080/10807030490887221
Deloitte. 2013. The Logistics Industry in Turkey. Deloitte Türkiye. 114 p. Available from Internet: http://www.invest.gov.tr/en-US/infocenter/publications/Documents/Transportation-Logistics-Industry.pdf
Demirel, T.; Demirel, N. Ç.; Kahraman, C. 2010. Multi-criteria warehouse location selection using Choquet integral, Expert Systems with Applications 37(5): 3943–3952. http://doi.org/10.1016/j.eswa.2009.11.022
Durmuş, A.; Turk, S. S. 2014. Factors influencing location selection of warehouses at the intra-urban level: istanbul case, European Planning Studies 22(2): 268–292. http://doi.org/10.1080/09654313.2012.731038
EC. 2011. White Paper: Roadmap to a Single European Transport Area – Towards a Competitive and Resource Efficient Transport System. COM(2011) 144 final. 28.3.2011, Brussels. Available from Internet: http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52011DC0144
Erdogan, S.; Yilmaz, I.; Baybura, T.; Gullu, M. 2008. Geographical information systems aided traffic accident analysis system case study: city of Afyonkarahisar, Accident Analysis & Prevention 40(1): 174–181. http://doi.org/10.1016/j.aap.2007.05.004
Erkayman, B.; Gundogar, E.; Akkaya, G.; Ipek, M. 2011. A fuzzy TOPSIS approach for logistics center location selection, Journal of Business Case Studies 7(3): 49–55. http://doi.org/10.19030/jbcs.v7i3.4263
Eryürük, S. H.; Kalaoğlu, F.; Baskak, M. 2012. A site selection model for establishing a clothing logistics center, Tekstil Ve Konfeksiyon 22(1): 40–47.
Getis, A.; Ord, J. K. 1992. The analysis of spatial association by use of distance statistics, Geographical Analysis 24(3): 189–206. http://doi.org/10.1111/j.1538-4632.1992.tb00261.x
Guasch, J. L.; Kogan, J. 2001. Inventories in Developing Countries: Levels and Determinants – a Red Flag for Competitiveness and Growth. Policy Research Working Paper No 2552. The World Bank, Washington, DC. 30 p. Available from Internet: http://www-wds.worldbank.org/servlet/WDSContentServer/WDSP/IB/2001/03/26/000094946_01031305310524/Rendered/PDF/multi0page.pdf
Gumus, I.; Onden, I. 2014. Using spatial information for international market alternatives ordering, in UNF International Business Conference on Teaching Research and Practice – 14, 21–22 February 2014, University of North Florida, Jacksonville, FL, 1–5.
Jankowski, P.; Richard, L. 1994. Integration of GIS-based suitability analysis and multicriteria evaluation in a spatial decision support system for route selection, Environment and Planning B: Planning and Design 21(3): 323–340. http://doi.org/10.1068/b210323
Jenks, G. F. 1967. The data model concept in statistical mapping, International Yearbook of Cartography 7: 186–190.
Kahraman, C.; Beskese, A.; Ruan, D. 2004. Measuring flexibility of computer integrated manufacturing systems using fuzzy cash flow analysis, Information Sciences 168(1–4): 77–94. http://doi.org/10.1016/j.ins.2003.11.004
Kahraman, C.; Kaya, İ.; Cebi, S. 2009. A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process, Energy 34(10): 1603–1616. http://doi.org/10.1016/j.energy.2009.07.008
Kahraman, C.; Süder, A.; Kaya, İ. 2014. Fuzzy multicriteria evaluation of health research investments, Technological and Economic Development of Economy 20(2): 210–226. http://doi.org/10.3846/20294913.2013.876560
Kayikci, Y. 2010. A conceptual model for intermodal freight logistics centre location decisions, Procedia – Social and Behavioral Sciences 2(3): 6297–6311. http://doi.org/10.1016/j.sbspro.2010.04.039
Kuo, R. J.; Chi, S. C.; Kao, S. S. 2002. A decision support system for selecting convenience store location through integration of fuzzy AHP and artificial neural network, Computers in Industry 47(2): 199–214. http://doi.org/10.1016/S0166-3615(01)00147-6
Levine, N. 2006. Crime mapping and the CrimeStat program, Geographical Analysis 38(1): 41–56. http://doi.org/10.1111/j.0016-7363.2005.00673.x
Liou, T.-S.; Wang, M.-J. J. 1992. Ranking fuzzy numbers with integral value, Fuzzy Sets and Systems 50(3): 247–255. http://doi.org/10.1016/0165-0114(92)90223-Q
Liu, N.; Huang, B.; Chandramouli, M. 2006. Optimal siting of fire stations using GIS and ANT algorithm, Journal of Computing in Civil Engineering 20(5): 361–369. http://doi.org/10.1061/(ASCE)0887-3801(2006)20:5(361)
Maister, D. H. 1976. Centralisation of inventories and the “square root law”, International Journal of Physical Distribution 6(3): 124–134. http://doi.org/10.1108/eb014366
McCoy, J.; Johnston, K.; Kopp, S.; Borup, B.; Willison, J. 2004. ArcGIS 9: Using ArcGIS Spatial Analyst. 4th edition. ESRI Press. 233 p.
McKinnon, A. 2009. The present and future land requirements of logistical activities, Land Use Policy 26(1): S293–S301. http://doi.org/10.1016/j.landusepol.2009.08.014
Mon, D.-L.; Cheng, C.-H.; Lin, J.-C. 1994. Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight, Fuzzy Sets and Systems 62(2): 127–134. http://doi.org/10.1016/0165-0114(94)90052-3
Nathanail, E. 2007. Developing an integrated logistics terminal network in the CADSES, Transition Studies Review 14(1): 125–146. http://doi.org/10.1007/s11300-007-0139-y
Ocalir, E. V.; Ercoskun, O. Y.; Tur, R. 2010. An integrated model of GIS and fuzzy logic (FMOTS) for location decisions of taxicab stands, Expert Systems with Applications 37(7): 4892–4901. http://doi.org/10.1016/j.eswa.2009.12.026
Onden, I.; Tuzla, H.; Cobb, S. 2012. Evaluation of retail store location alternatives for investment decisions using the Delphi technique and geographic information systems, International Business: Research, Teaching and Practice 6(2): 64–75.
Özcan, T.; Çelebi, N.; Esnaf, Ş. 2011. Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem, Expert Systems with Applications 38(8): 9773–9779. http://doi.org/10.1016/j.eswa.2011.02.022
Özdemir, D. 2010. Strategic choice for Istanbul: a domestic or international orientation for logistics?, Cities 27(3): 154–163. http://doi.org/10.1016/j.cities.2009.12.003
Purba, J. H.; Lu, J.; Ruan, D.; Zhang, G. 2010. A Hybrid approach for fault tree analysis combining probabilistic method with fuzzy numbers, Lecture Notes in Computer Science 6113: 194–201. http://doi.org/10.1007/978-3-642-13208-7_25
Rantasila, K.; Ojala, L. 2012. Measurement of national-level logistics costs and performance, International Transport Forum Discussion Papers 4: 1–62. http://doi.org/10.1787/5k8zvv79pzkk-en
RTMTMC. 2014. Deniz Ticareti 2013 İstatistikleri: Deniz Taşıtları, Denizyolu Taşıma Ve Teşvik İstatistikleri. Republic of Türkiye Ministry of Transport, Maritime and Communications (RTMTMC). 99 s. Available from Internet: http://www.ubak.gov.tr/BLSM_WIYS/DTGM/tr/Kitaplar/20140613_162122_64032_1_64480.pdf (in Turkish).
Rodrigue, J.-P.; Comtois, C.; Slack, B. 2013. The Geography of Transport Systems. 3rd edition. Routledge. 432 p.
Rodrigues, A. M.; Bowersox, D. J.; Calantone, R. J. 2005. Estimation of global and national logistics expenditures: 2002 data update, Journal of Business Logistics 26(2): 1–16. http://doi.org/10.1002/j.2158-1592.2005.tb00202.x
Saaty, T. L. 1990. How to make a decision: the analytic hierarchy process, European Journal of Operational Research 48(1): 9–26. http://doi.org/10.1016/0377-2217(90)90057-I
Saaty, T. L. 2008. Decision making with the analytic hierarchy process, International Journal of Services Sciences 1(1): 83–98. http://doi.org/10.1504/IJSSCI.2008.017590
Sengpiehl, C.; Wu, Y.; Nagel, P. 2009. Logistics cities: a spatial requirement framework, in Proceedings of the 14th International Symposium on Logistics (14th ISL), 5–8 July 2009, Istanbul, Turkey, 586–594.
Truong, L.T.; Somenahalli, S. V. C. 2011. Using GIS to identify pedestrian-vehicle crash hot spots and unsafe bus stops, Journal of Public Transportation 14(1): 99–114. http://doi.org/10.5038/2375-0901.14.1.6
Tsamboulas, D. A.; Kapros, S. 2003. Freight village evaluation under uncertainty with public and private financing, Transport Policy 10(2): 141–156. http://doi.org/10.1016/S0967-070X(03)00002-7
TUIK. 2014a. Address Based Population Registration System. Turkish Statistical Institute (TUIK). Available from Internet: http://www.turkstat.gov.tr
TUIK. 2014b. Foreign Trade Statistics: Foreign Trade by Years. Turkish Statistical Institute (TUIK). Available from Internet: http://www.turkstat.gov.tr
Uçal Sarı, I.; Öztayşi, B.; Kahraman, C. 2013. Fuzzy analytic hierarchy process using type-2 fuzzy sets: an application to warehouse location selection, in M. Doumpos, E. Grigoroudis (Eds.). Multicriteria Decision Aid and Artificial Intelligence: Links, Theory and Applications, 285–308. http://doi.org/10.1002/9781118522516.ch12
UTIKAD. 2012. Türk Lojistik Sektörü Değerlendirmesi. Association of International Forwarding and Logistics Service Providers (UTIKAD). 61 p. Available from Internet: http://www.utikad.org.tr/db/files/TurkLojistikSektoruDegerlendirmesi.pdf (in Turkish).
Vahidnia, M. H.; Alesheikh, A. A.; Alimohammadi, A. 2009. Hospital site selection using fuzzy AHP and its derivatives, Journal of Environmental Management 90(10): 3048–3056. http://doi.org/10.1016/j.jenvman.2009.04.010
Van Laarhoven, P. J. M.; Pedrycz, W. 1983. A fuzzy extension of Saaty’s priority theory, Fuzzy Sets and Systems 11(1–3): 229–241. http://doi.org/10.1016/S0165-0114(83)80082-7
Vlachopoulou, M.; Silleos, G.; Manthou, V. 2001. Geographic information systems in warehouse site selection decisions, International Journal of Production Economics 71(1–3): 205–212. http://doi.org/10.1016/S0925-5273(00)00119-5
Wang, Y.-M.; Luo, Y.; Hua, Z. 2008. On the extent analysis method for fuzzy AHP and its applications, European Journal of Operational Research 186(2): 735–747. http://doi.org/10.1016/j.ejor.2007.01.050
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