A Grey DEMATEL Integrated Approach to Determine Third Party Logistics Service Provider Selection Criteria

Year 2018, Volume 6, Issue 2, 2018, 277 - 292, 31.12.2018

Ejder Ayçin

https://doi.org/10.17093/alphanumeric.418829

Cited By: 5

Abstract

Third-party logistics (3PL) services have seen significant growth in recent years as a result of playing a key role in supply chain management. The demand for 3PL service providers has increased as companies offer better service to their customers, lower costs and gain competitive advantage. This paper includes an application that will help determine the most important criteria in the selection and evaluation of 3PL service providers. The aim of the paper is to be able to determine the selection criteria of the 3PL service providers and the relationships between them, from the point of view of companies already using logistics services outsourcing. For this purpose, grey system theory and DEMATEL approach are integrated in order to describe uncertain and complex decisions with definite numerical values and determine the relations and importance levels between the criteria. The findings revealed interrelations between criteria and presented the most important criteria for 3PL provider selection. It is believed that the results of the paper will help the managers to propose a model that can be implemented with the selection criteria of the 3PL service provider.

Keywords

Third-Party Logistics, Grey Systems Theory, DEMATEL

Üçüncü Parti Lojistik Hizmet Sağlayıcı Seçim Kriterlerinin Gri DEMATEL Bütünleşik Yaklaşımıyla Belirlenmesi

Abstract

Üçüncü parti lojistik (3PL) hizmetlerinin, tedarik zinciri yönetiminde temel bir rol oynamasının sonucu olarak son yıllarda kayda değer bir büyüme yaşadığı görülmektedir. 3PL hizmet sağlayıcılarına yönelik talep, şirketlerin müşterine daha iyi hizmetleri sunmaları, maliyetleri düşürmeleri ve rekabet üstünlüğü elde etmeleri gibi avantajlar sağladığı için artış göstermektedir. Bu makalede, 3PL hizmet sağlayıcısı seçimi ve değerlendirilmesi sürecindeki en önemli kriterlerin belirlenmesine yardımcı olacak bir uygulamaya yer verilmiştir. Makalenin amacı, lojistik hizmetlerini zaten dış kaynak kullanan firmaların bakış açısıyla 3PL hizmet sağlayıcılarının seçim kriterlerini ve aralarındaki ilişkileri belirleyebilmektir. Bu amaç doğrultusunda belirsiz ve karmaşık kararları kesin sayısal değerler ile betimleyebilmek ve kriterler arasındaki ilişkileri ve önem düzeylerini tespit edebilmek için gri sistem teorisi ile DEMATEL yaklaşımı bütünleşik olarak ele alınmıştır. Bulgular, kriterler arasındaki karşılıklı ilişkileri ortaya koyarak 3PL hizmet sağlayıcısı seçimindeki en önemli kriterleri ortaya koymuştur. Makale sonuçlarının yöneticilere, 3PL hizmet sağlayıcısı seçim kriterlerinin belirlenmesinde uygulanabilecek bir model önerisiyle yardımcı olacağı düşünülmektedir.

Keywords

Üçüncü Parti Lojistik, Gri Sistem Teorisi, DEMATEL

References

• Almeida, A T. (2007). Multicriteria decision model for outsourcing contracts selection based on utility function and ELECTRE method. Computers and Operations Research, 34(12): 3569–74.
• Aghazadeh, S M. (2003). How to choose an effective third party logistics provider? Management Research News, 26(7): 50–8.
• Aguezzoul, A., Rabenasolo, B., Jolly-Desodt, A.M. (2006). Multicriteria decision aid tool for third-party logistics provider’s selection, Proceedings of the IEEE International Conference on Service Systems and Service Management, Troyes, October 25-27, pp. 912-916.
• Anderson, E.J., Colman,T., Devinney, T.M., Keating, B. (2011). What drives the choice of third-party logistics provider? Journal of Supply Chain Management, 47(2): 97–115.
• Awasthi, A., Baležentis, T. (2017). A hybrid approach based on BOCR and fuzzy MULTIMOORA for logistics service provider selection. International Journal of Logistics Systems and Management, 27(3): 261-282.
• Bai, C., Sarkis, J. (2010). Integrating sustainability into supplier selection with grey system and rough set methodologies. International Journal of Production Economics, 124(1): 252-264.
• Bottani, E, Rizzi, A. (2006). A fuzzy TOPSIS methodology to support outsourcing of logistics services. Supply Chain Management: An International Journal, 11(4): 294–308.
• Büyüközkan, G. Feyzioğlu, O., Nebol, E. (2008). Selection of the strategic alliance partner in logistics value chain. International Journal of Production Economics, 113(1): 148–58.
• Chen, C.H., Tzeng, G.H. (2011). Assessment Model for Improving Educational Curriculum Materials Based on The DANP Technique with Grey Relational Analysis. International Journal of Information Systems for Logistics and Management, 6(2): 23-36.
• Chen, F.-H., Hsu, T.-S., Tzeng, G.-H. (2011). A Balanced Scorecard Approach to Establish a Performance Evaluation and Relationship Model for Spring Hotels Based on a Hybrid MCDM Model Combining DEMATEL and ANP. International Journal of Hospitality Management, 30: 908-932.
• Cheng, Y.H, Lee, F. (2010). Outsourcing reverse logistics of high-tech manufacturing firms by using a systematic decision-making approach: TFT-LCD sector in Taiwan. Industrial Marketing Management, 39(7): 1111–9.
• Deng, J.L. (1989). Introduction to Grey System Theory. Journal of Grey Systems, 1(1): 1-24.
• Dou, Y., Zhu, Q., Sarkis, J. (2014). Evaluating green supplier development programs with a grey-analytical network process-based methodology. European Journal of Operational Research, 233(2): 420-431.
• Ecer, F. (2017). Third-party logistics (3PLs) provider selection via Fuzzy AHP and EDAS integrated model. Technological and Economic Development of Economy, 1-20.
• Efendigil, T, Önüt, S, Kongar, E. (2008). A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness. Computers and Industrial Engineering, 54(2): 269–87.
• Falsini, D., Fondi, F., Schiraldi, M.M. (2012). A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration. International Journal of Production Research, 50(17): 4822–9.
• Garside, A. K., Saputro, T. E. (2017). Evaluation and selection of 3PL provider using fuzzy AHP and grey TOPSIS in group decision making. In AIP Conference Proceedings, 1902(1): 020056). AIP Publishing.
• Garg, K., Agarwal, V., Jha, P.C. (2015). Transportation decision making through logistics outsourcing and 3PL selection in an integrated closed-loop supply chain. Proceedings of Fourth International Conference on Soft Computing for Problem Solving, Springer, January, pp. 473-485.
• Hamdan A, Rogers, KJ. (2008). Evaluating the efficiency of 3PL logistics operations. International Journal of Production Economics, 113(1): 235–44.
• Ho W, He, T., Lee, C.K.M., Emrouznejad, A. (2012). Strategic logistics outsourcing: an integrated QFD and fuzzy AHP approach. Expert Systems with Applications, 39(12): 10841–50.
• Hsu, C.C, Liou, J.J.H., Chuang, YC. (2013). Integrating DANP and modified grey relation theory for the selection of an outsourcing provider. Expert Systems with Applications, 40(6): 2297–304.
• Jharkharia, S, Shankar, R. (2007). Selection of logistics service provider: An analytic Network process(ANP) approach. Omega: The International Journal of Management Science, 35(3):274–89.
• Kannan G, Pokharel S, Kumar, P.S. (2009). A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider. Resources, Conservation and Recycling, 54(1): 28–36.
• Knemeyer A.M., Murphy, P.R. (2004). Evaluating the performance of third-party logistics arrangements:a relationship marketing perspective. Journal of Supply Chain Management, 40(4): 35–51.
• Li, C.W., Tzeng, G.H. (2009). Identification of a Threshold Value for the DEMATEL Method Using the Maximum Mean De-Entropy Algorithm to Find Critical Services Provided by A Semiconductor Intellectual Property Mall. Expert Systems with Applications, 36(6): 9891-9898.
• Li, P., Tan, T. C., Lee, J. Y. (1997). Grey Relational Analysis of Amine Inhibition of Mild Steel Corrosion in Acids. Corrosion, 53(3): 186-194.
• Liou, J.J.H., Chuang, Y.T. (2010). Developing a hybrid multi-criteria model for selection of outsourcing providers. Expert Systems with Applications, 37(5): 3755–61.
• Liu, H.T., Wang, W.K. (2009). An integrated fuzzy approach for provider evaluation and selection in third-party logistics”, Expert Systems with Applications, 36(3): 4387-4398.
• Liu, S., Lin, Y. (2006). Grey Information: Theory and Practical Applications, Springer Verlag, London.
• Opricovic, S., Tzeng, G.H. (2003). Defuzzification within a multicriteria decision model”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(5): 635-652.
• Özdemir, A., Tüysüz, F. (2015). A grey-based DEMATEL approach for analyzing the strategies of universities: a case of Turkey, 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), pp. 1-6.
• Perçin, S, Min, H. (2013). A hybrid quality function deployment and fuzzy decision- making methodology for the optimal selection of third-party logistics service providers. International Journal of Logistics Research and Applications, 16(5):380–97.
• Raut, R.D., Kharat, M.G., Kamble, S.S., Kamble, S.J., Desai, R. (2018). Evaluation and selection of third-party logistics providers using an integrated multi-criteria decision making approach. International Journal of Services and Operations Management, 29(3): 373-392.
• Sheen, G.L, Tai, C.T. (2006). A study on decision factors and third party selection criterion of logistics outsourcing: An exploratory study of direct selling industry. The Journal of American Academy of Business, Cambridge, 9(2): 331–7.
• Singh, R. K., Gunasekaran, A., Kumar, P. (2017). Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach. Annals of Operations Research, 1-23.
• Tseng, M.L., Lin, Y.H. (2009). Application of Fuzzy DEMATEL to Develop a Cause and Effect Model of Municipal Solid Waste Management in Metro Manila. Environmental Monitoring and Assessment. 158: 519-533.
• Tseng, M.L. (2009). A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach. Expert Systems with Applications, 36(4): 7738-7748.
• Tzeng, G.H., Chiang, C.H., Li, C.W. (2007). Evaluating Intertwined Effects in E-Learning Programs: A Novel Hybrid MCDM Model Based nn Factor Analysis and DEMATEL. Expert systems with Applications, 32(4): 1028-1044.
• Wang, X., Persson, G., Huemer, L. (2014). Logistics service providers and value creation through collaboration: a case study”, Long Range Planning, 49(1): 117-128.
• Wang, Y.L., Tzeng, G.H. (2012). Brand Marketing for Creating Brand Value Based on A MCDM Model Combining DEMATEL with ANP and VIKOR Methods. Expert Systems with Applications. 39: 5600-5615.
• Wong, C.Y., Karia, N. (2010). Explaining the competitive advantage of logistics service providers: a resource-based view approach. International Journal of Production Economics, 128(1): 51-67.
• Xia, X., Govindan, K., Zhu, Q. (2015). Analyzing internal barriers for automotive parts remanufacturers in China using grey-DEMATEL approach. Journal of Cleaner Production, 87(1): 811-825.
• Yayla, A.Y., Öztekin, A., Gümüş, A.T., Gunasekaran, A. (2015). A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making”, International Journal of Production Research, 53(20): 6097-6113.
• Yeung, A.C.L. (2006). The impact of third-party logistics performanc eon the logistics and export performance of users:an empirical study. Maritime Economics and Logistics, 8(2):121–39.
• Zhou, T., Chen, J., Qiao, Z. (2003). The competition ability index system and vague evaluation of third-party logistics corporation”, Logistics Management, 26(5): 30-32.