Share:


An assessment approach for non-governmental organizations in humanitarian relief logistics and an application in Turkey

    Erkan Celik Affiliation
    ; Alev Taskin Gumus Affiliation

Abstract

The ever-increasing natural disasters have been causing the loss of lives, properties and resources. By the preparedness and response ability of non-governmental organizations, it is aimed to minimize these losses. In this paper, first, the critical success factors of humanitarian relief logistics management operations are determined and categorized. Then, by considering these factors, a hybrid method that consists of trapezoidal interval type-2 fuzzy sets, AHP and TOPSIS, is proposed to evaluate emergency preparedness and response ability performance of non-governmental relief organizations. The proposed hybrid method is applied for non-governmental relief organizations in Turkey to evaluate their performance, and to the factors need to be improved for each determined organization.


First published online 11 September 2015 

Keyword : non-governmental relief organizations, emergency management, multiple criteria, trapezoidal interval type-2 fuzzy sets, AHP, TOPSIS

How to Cite
Celik, E., & Taskin Gumus, A. (2018). An assessment approach for non-governmental organizations in humanitarian relief logistics and an application in Turkey. Technological and Economic Development of Economy, 24(1), 1-26. https://doi.org/10.3846/20294913.2015.1056277
Published in Issue
Jan 17, 2018
Abstract Views
1740
PDF Downloads
1357
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abidi, H.; de Leeuw, S.; Klumpp, M. 2013. Measuring success in humanitarian supply chains, International Journal of Business and Management Invention 2: 31–39

Abidi, H.; de Leeuw, S.; Klumpp, M. 2014. Humanitarian supply chain performance management: a systematic literature review, Supply Chain Management: An International Journal 19: 592–608. http://dx.doi.org/10.1108/SCM-09-2013-0349

Aiello, G.; Enea, M.; Galante, G.; La Scalia, G. 2009. Clean agent selection approached by fuzzy TOPSIS decision-making method, Fire Technology 45: 405–418. http://dx.doi.org/10.1007/s10694-008-0059-3

Apte, A. 2009. Humanitarian logistics: a new field of research and action, foundations and trends in technology, Information and Operations Management 3(1): 1–100. http://dx.doi.org/10.1561/0200000014

Balcik, B.; Beamon, B. M.; Krejci, C. C.; Muramatsu, K. M.; Ramirez, M. 2010. Coordination in humanitarian relief chains: practices, challenges and opportunities, International Journal of Production Economics 126(1): 22–34. http://dx.doi.org/10.1016/j.ijpe.2009.09.008

Balcik, B.; Beamon, B. M. 2008. Facility location in humanitarian relief, International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management 11(2): 101–121. http://dx.doi.org/10.1080/13675560701561789

Beamon, B. M.; Balcik, B. 2008. Performance measurement in humanitarian relief chains, International Journal of Public Sector Management 21(1): 4–25. http://dx.doi.org/10.1108/09513550810846087

Beamon, B. M.; Kotleba, S. A. 2006. Inventory management support systems for emergency humanitarian relief operations in South Sudan, The International Journal of Logistics Management 17(2): 187–212. http://dx.doi.org/10.1108/09574090610689952

Behzadian, M.; Khanmohammadi Otaghsara, S.; Yazdani, M.; Ignatius, J. 2012. A state-of the-art survey of TOPSIS applications, Expert Systems with Applications 39(17): 13051–13069. http://dx.doi.org/10.1016/j.eswa.2012.05.056

Buckley, J. J. 1985. Fuzzy hierarchical analysis, Fuzzy Sets and Systems 17: 233–247. http://dx.doi.org/10.1016/0165-0114(85)90090-9

Bui, T.; Cho, S.; Sankaran, S.; Sovereign, M. 2000. A framework for designing a global information network for multinational humanitarian assistance/disaster relief, Information Systems Frontiers 1(4): 427–442. http://dx.doi.org/10.1023/A:1010074210709

Buyukozkan, G.; Feyzioglu, O.; Nebol, E. 2008. Selection of the strategic alliance partner in logistics value chain, International Journal of Production Economics 113: 148–158. http://dx.doi.org/10.1016/j.ijpe.2007.01.016

Celik, E.; Bilisik, O. N.; Erdogan, M.; Gumus, A. T.; Baracli, H. 2013b. An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul, Transportation Research Part E: Logistics and Transportation Review 58: 28–51. http://dx.doi.org/10.1016/j.tre.2013.06.006

Celik, E.; Gul, M.; Gumus, A. T.; Guneri, A. F. 2012. A fuzzy TOPSIS approach based on trapezoidal numbers to material selection problem, Journal of Information Technology Applications & Management 19(3): 19–30.

Celik, E.; Gumus, A. T.; Alegoz, A. 2013a. A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management, in Proc. of the 3rd International Fuzzy Systems Symposium (FUZZYSS’13), 24–25 October 2013, Istanbul, Turkey, 168–173.

Chen, C. T. 2000. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems 114(1): 1–9. http://dx.doi.org/10.1016/S0165-0114(97)00377-1

Chen, S. J.; Hwang, C. L. 1992. Fuzzy multiple attribute decision making: methods and applications. Berlin: Springer-Verlag. http://dx.doi.org/10.1007/978-3-642-46768-4

Chen, S. M.; Lee, L. W. 2010. Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method, Expert Systems with Applications 37(4): 2790–2798. http://dx.doi.org/10.1016/j.eswa.2009.09.012

Chia, E. S. 2007. Engineering disaster relief, IEEE Technology and Society Magazine 2007 (Fall): 24–29. http://dx.doi.org/10.1109/MTS.2007.906673

Daniel, D. R. 1961. Management information crisis, Harvard Business Review 39(5): 111–121.

Davidson, A. L. 2006. Key performance indicators in humanitarian logistics: Master Thesis of Engineering in Logistics. Massachusetts Institute of Technology, Cambridge, MA.

Disparte, D. 2007. The postman’s parallel, Car Nation 2: 22–27.

Döyen, A.; Aras, N.; Barbarosoğlu, G. 2012. A two-echelon stochastic facility location model for humanitarian relief logistics, Optimization Letters 6(6): 1123–1145. http://dx.doi.org/10.1007/s11590-011-0421-0

Duran, S.; Gutierrez, M. A.; Keskinocak, P. 2011. Pre-positioning of emergency items for CARE international, Interfaces 41(3): 223–237. http://dx.doi.org/10.1287/inte.1100.0526

EM-DAT. 2013. EM-DAT – Emergency Events Database. Centre for Research on the Epidemiology of Disasters (CRED), Universite´ Catholique de Louvain, Louvain-La-Neuve [online], [cited 15 May 2013]. Available from internet: www.emdat.be

Ertugrul, I.; Karakasoglu, N. 2008. Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection, International Journal of Advanced Manufacturing Technology 39: 783–795. http://dx.doi.org/10.1007/s00170-007-1249-8

Freund, Y. P. 1988. Critical success factors, Strategy & Leadership 16(4): 20–23. http://dx.doi.org/10.1108/eb054225

Fritz Institute. 2005. Logistics and the effective delivery of humanitarian relief. Fritz Institute, San Francisco, CA. 12 p.

Garcia-Cascales, M. S.; Lamata, M. T. 2009. Multi-criteria analysis for a maintenance management problem in an engine factory: rational choice, Journal of Intelligent Manufacturing 22(5): 779–788. http://dx.doi.org/10.1007/s10845-009-0290-x

Gumus, A. T. 2009. Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology, Expert Systems with Applications 36(2): 4067–4074. http://dx.doi.org/10.1016/j.eswa.2008.03.013

Gumus, A. T.; Yayla, A. Y.; Çelik, E.; Yildiz, A. 2013. A combined Fuzzy-AHP and Fuzzy-GRA methodology for hydrogen energy storage method selection in Turkey, Energies 6(6): 3017–3032. http://dx.doi.org/10.3390/en6063017

Gunasekaran, A.; Ngai, E. W. T. 2003. The successful management of a small logistics company, International Journal of Physical Distribution & Logistics Management 33(9): 825–842. http://dx.doi.org/10.1108/09600030310503352

Gunnec, D.; Salman, F. S. 2007. A two-stage multi-criteria stochastic programming model for location of emergency response and distribution centers, in Proc. of the International Network Optimization Conference (INOC), 22–25 April 2007, Spa, Belgium.

Holland, C. R.; Light, B. 1999. A critical success factors model for ERP implementation, IEEE Software 16(3): 30–36. http://doi.ieeecomputersociety.org/10.1109/52.765784

Hwang, C. L.; Yoon, K. 1981. Multiple attribute decision making-methods and applications. Heidelberg: Springer-Verlag. http://dx.doi.org/10.1007/978-3-642-48318-9

Jia, H.; Ordóñez, F.; Dessouky, M. 2007. A modeling framework for facility location of medical services for large-scale emergencies, IIE Transactions 39(1): 41–55. http://dx.doi.org/10.1080/07408170500539113

Jolai, F.; Yazdian, S. A.; Shahanaghi, K.; Azari-Khojasteh, M. 2011. Integrating fuzzy TOPSIS and multiperiod goal programming for purchasing multiple products from multiple suppliers, Journal of Purchasing & Supply Management 17: 42–53. http://dx.doi.org/10.1016/j.pursup.2010.06.004

Ju, Y.; Wang, A.; Liu, X. 2012. Evaluating emergency response capacity by fuzzy AHP and 2-tuple fuzzy linguistic approach, Expert Systems with Applications 39(8): 6972–6981. http://dx.doi.org/10.1016/j.eswa.2012.01.061

Kahraman, C.; Suder, A.; Cebi, S. 2013. Fuzzy multi-criteria and multi-experts evaluation of government investments in higher education: the case of Turkey, Technological and Economic Development of Economy 19(4): 549–569. http://dx.doi.org/10.3846/20294913.2013.837110

Kovacs, G.; Spens, K. M. 2007. Humanitarian logistics in disaster relief operations, International Journal of Physical Distribution and Logistics Management 37: 99–114. http://dx.doi.org/10.1108/09600030710734820

Lee, L. W.; Chen, S. M. 2008. Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets, in Proc. of the 7thInternational Conference on Machine Learning and Cybernetic, 12–15 July 2008, Kumming, China, 3260–3265.

Leiras, A.; de Brito Jr, I.; Peres, E. Q.; Bertazzo, T. R.; Yoshizaki, H. T. Y. 2014. Literature review of humanitarian logistics research: trends and challenges, Journal of Humanitarian Logistics and Supply Chain Management 4(1): 95–130. http://dx.doi.org/10.1108/JHLSCM-04-2012-0008

Li, T.; Jin, J.; Li, C. 2012. Refractured well selection for multicriteria group decision making by integrating fuzzy AHP with fuzzy TOPSIS based on interval-typed fuzzy numbers, Journal of Applied Mathematics, 1–21. http://dx.doi.org/10.1155/2012/304287

Lu, D. K.; Pettit, S.; Beresford, A. 2006. Critical success factors for emergency relief logistics, Whampoa: An Interdisciplinary Journal 51(1): 177–184.

Mardani, A.; Jusoh, A.; Zavadskas, E. K. 2015. Fuzzy multiple criteria decision-making techniques and applications – two decades review from 1994 to 2014, Expert Systems with Applications 42(8): 4126–4148. http://dx.doi.org/10.1016/j.eswa.2015.01.003

Marx, M. 2009. Coordinating international response to humanitarian crises, in Proceedings of Humanitarian Logistics Conference, 19–20 February 2009, Georgia, Atlanta. H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, Atlanta, USA.

Mendel, J. M.; John, R. I.; Liu, F. 2006. Interval type-2 fuzzy logic systems made simple, Fuzzy Systems, IEEE Transactions on 14(6): 808–821. http://dx.doi.org/10.1109/TFUZZ.2006.879986

Moe, T. L.; Gehbauer, F.; Senitz, S.; Mueller, M. 2007. Balanced scorecard for natural disaster management projects, Disaster Prevention and Management: An International Journal 16(5): 785–806. http://dx.doi.org/10.1108/09653560710837073

Moe, T. L.; Pathranarakul, P. 2006. An integrated approach to natural disaster management: public project management and its critical success factors, Disaster Prevention and Management: An International Journal 15(3): 396–413. http://dx.doi.org/10.1108/09653560610669882

Nasab, F. G.; Rostamy-Malkhalifeh, M. 2010. Extension of TOPSIS for group decision-making based on the type-2 fuzzy positive and negative ideal solutions, International Journal of Industrial Mathematics 2(3): 199–213.

Natarajarathinam, M.; Capar, I.; Narayanan, A. 2009. Managing supply chains in times of crisis: a review of literature and insights, International Journal of Physical Distribution & Logistics Management 39(7): 535–573. http://dx.doi.org/10.1108/09600030910996251

Oloruntoba, R. 2005. A wave of destruction and the waves of relief: issues, challenges and strategies, Disaster Prevention and Management: An International Journal 4: 506–521. http://dx.doi.org/10.1108/09653560510618348

Oloruntoba, R. 2010. An analysis of the Cyclone Larry emergency relief chain: some key success factors, International Journal of Production Economics 126: 85–101. http://dx.doi.org/10.1016/j.ijpe.2009.10.013

Onut, S.; Soner, S. 2008. Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment, Waste Management 28: 1552–1559. http://dx.doi.org/10.1016/j.wasman.2007.05.019

Pettit, S.; Beresford, A. 2009. Critical success factors in the context of humanitarian aid supply chains, International Journal of Physical Distribution & Logistics Management 39(6): 450–468. http://dx.doi.org/10.1108/09600030910985811

Pettit, S. J.; Beresford, A. K. C. 2005. Emergency relief logistics: an evaluation of military, non-military and composite response models, International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management 8(4): 313–331. http://dx.doi.org/10.1080/13675560500407325

Power, D.; Amrik, J.; Sohal, S.; Rahman, S. U. 2001. Critical success factors in agile supply chain management – an empirical study, International Journal of Physical Distribution & Logistics Management 31(4): 247–265. http://dx.doi.org/10.1108/09600030110394923

Rathod, M. K.; Kanzaria, H. V. 2011. A methodological concept for phase change material selection based on multiple criteria decision analysis with and without fuzzy environment, Materials and Design 32: 3578–3585. http://dx.doi.org/10.1016/j.matdes.2011.02.040

Rawls, C. G.; Turnquist, M. A. 2010. Pre-positioning of emergency supplies for disaster response, Transportation Research Part B: Methodological 44(4): 521–534. http://dx.doi.org/10.1016/j.trb.2009.08.003

Rostamzadeh, R.; Sofian, S. 2011. Prioritizing effective 7Ms to improve production systems performance using fuzzy AHP and fuzzy TOPSIS (case study), Expert Systems with Applications 38: 5166–5177. http://dx.doi.org/10.1016/j.eswa.2010.10.045

Saaty, T. L. 1980. The analytic hierarchy process. New York: McGraw-Hill.

Sandwell, C. 2011. A qualitative study exploring the challenges of humanitarian organisations, Journal of Humanitarian Logistics and Supply Chain Management 1(2): 132–150. http://dx.doi.org/10.1108/20426741111158430

Seneviratne, K.; Baldry, D.; Pathirage, C. 2010. Disaster knowledge factors in managing disasters successfully, International Journal of Strategic Property Management 14(4): 376–390 http://dx.doi.org/10.3846/ijspm.2010.28

Sumner, M. 1999. Critical success factors in enterprise wide information management systems projects, in Proc. of the 1999 ACM SIGCPR Conference on Computer Personnel Research, 1999, New York, USA, 297–303.

Sun, C. C. 2010. A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods, Expert Systems with Applications 37: 7745–7754. http://dx.doi.org/10.1016/j.eswa.2010.04.066

Tomasini, R. M.; Van Wassenhove, L. N. 2009. Humanitarian logistics. New York: INSEAD Business Press. http://dx.doi.org/10.1057/9780230233485

Tsaur, S. H.; Chang, T. Y.; Yen, C. H. 2002. The evaluation of airline service quality by fuzzy MCDM, Tourism Management 23: 107–115. http://dx.doi.org/10.1016/S0261-5177(01)00050-4

Van Wassenhove, L. N.; Pedraza Martinez, A. J. 2012. Using OR to adapt supply chain management best practices to humanitarian logistics, International Transactions in Operational Research 19(1–2): 307–322. http://dx.doi.org/10.1111/j.1475-3995.2010.00792.x

Wang, J. W.; Cheng, C. H.; Huang, K. C. 2009. Fuzzy hierarchical TOPSIS for supplier selection, Applied Soft Computing 9: 377–386. http://dx.doi.org/10.1016/j.asoc.2008.04.014

Whybark, D. C. 2007. Issues in managing disaster relief inventories, International Journal of Production Economics 108(1): 228–235. http://dx.doi.org/10.1016/j.ijpe.2006.12.012

Yoon, K. P.; Hwang, C. L. 1995. Multiple attribute decision making. Thousand Oaks, CA: Sage Publication.

Yushimito, W. F.; Jaller, M.; Ukkusuri, S. 2012. A Voronoi-based heuristic algorithm for locating distribution centers in disasters, Networks and Spatial Economics 12(1): 21–39. http://dx.doi.org/10.1007/s11067-010-9140-9

Zavadskas, E. K.; Turskis, Z.; Kildienė, S. 2014. State of art surveys of overviews on MCDM/MADM methods, Technological and Economic Development of Economy 20(1): 165–179. http://dx.doi.org/10.3846/20294913.2014.892037

Zeydan, M.; Çolpan, C.; Çobanoglu, C. 2011. A combined methodology for supplier selection and performance evaluation, Expert Systems with Applications 38: 2741–2751. http://dx.doi.org/10.1016/j.eswa.2010.08.064

Zhou, Q.; Weilai, H.; Ying, Z. 2011. Identifying critical success factors in emergency management using a fuzzy DEMATEL method, Safety Science 49(2): 243–252. http://dx.doi.org/10.1016/j.ssci.2010.08.005