Evaluation and Ranking of Sustainable Third-party Logistics Providers using the D-Analytic Hierarchy Process

Document Type : Original Article


School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran


Nowadays, the relative importance of logistics and sustainable supply chain cannot be denied and third-party logistics as one of the logistics management strategies can play an important role for many industry owners to consider their sustainability goals. The goal of this paper is to choose the best third-party logistics provider to achieve a sustainable logistics system, because third-party logistics service is mainly dependent on both transportation and workforces, managing them is one of the important issues of sustainability. Thus, third-party logistics providers need to be concerned about not only the economic criteria but also issues related to environmental and social sustainability in addition to two other dimensions namely technical and reputation. In this paper, a comprehensive classification of related criteria, sub-criteria, and sub-sub-criteria is proposed according to selecting the best third-party logistics provider. To evaluate and rank the proposed criteria, a D Number-Analytic Hierarchy Process method, as one of the proper and popular multi-criteria decision-making (MCDM) approaches, is utilized. Besides, a case study in dairy industry has been accomplished in the real-world to show the effectiveness and a better understanding of the proposed conceptual model. Finally, the best third-party logistics provider was identified among the alternatives for the proposed case study. The results showed that the proposed method could be a good alternative to conduct evaluations and the related sensitivity analysis, considering sustainability.


1.     Fazlollahtabar, H. Supply Chain Management Models: Forward, Reverse, Uncertain, and Intelligent Foundations with Case Studies. CRC Press, 2018.
2.     Wang, G., Dou, W., Zhu, W., and Zhou, N. “The effects of firm capabilities on external collaboration and performance: The moderating role of market turbulence.” Journal of Business Research, Vol. 68, No. 9, (2015), 1928–1936. https://doi.org/10.1016/j.jbusres.2015.01.002
3.     Ross, D. F. Distribution Planning and Control, Springer, 2015. https://doi.org/10.1007/978-1-4419-8939-0
4.     Beiki, H., Seyedhosseini, S. M., Ghezavati, V. R., and Seyedaliakbar, S. M. “Multi-objective optimization of multi-vehicle relief logistics considering satisfaction levels under uncertainty.” International Journal of Engineering, Transactions B: Applications, Vol. 33, No. 5, (2020), 814–824. https://doi.org/10.5829/IJE.2020.33.05B.13
5.     Kannan, G., Pokharel, S., and Kumar, P. S. “A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider.” Resources, Conservation and Recycling, Vol. 54, No. 1, (2009), 28–36. https://doi.org/10.1016/j.resconrec.2009.06.004
6.     Gharaei, A., and Jolai, F. “A multi-agent approach to the integrated production scheduling and distribution problem in multi-factory supply chain.” Applied Soft Computing Journal, Vol. 65, (2018), 577–589. https://doi.org/10.1016/j.asoc.2018.02.002
7.     Ageron, B., Gunasekaran, A., and Spalanzani, A. “Sustainable supply management: An empirical study.” International Journal of Production Economics, Vol. 140, No. 1, (2012), 168–182. https://doi.org/10.1016/j.ijpe.2011.04.007
8.     Tideman, S. G., C. Arts, M., and Zandee, D. P. “Sustainable Leadership: Towards a Workable Definition.” Journal of Corporate Citizenship, Vol. 49, (2013), 13–33. Retrieved from https://www.jstor.org/stable/jcorpciti.49.17?seq=1
9.     Baruffaldi, G., Accorsi, R., and Manzini, R. “Warehouse management system customization and information availability in 3pl companies: A decision-support tool.” Industrial Management and Data Systems, Vol. 119, No. 2, (2019), 251–273. https://doi.org/10.1108/IMDS-01-2018-0033
10.   Zarbakhshnia, N., Soleimani, H., and Ghaderi, H. “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 Journal, Vol. 65, , (2018), 307–319. https://doi.org/10.1016/j.asoc.2018.01.023
11.   Raut, R., Narkhede, B. E., Gardas, B. B., and Luong, H. T. “An ISM approach for the barrier analysis in implementing sustainable practices: The Indian oil and gas sector.” Benchmarking, Vol. 25, No. 4, (2018), 1245–1271. https://doi.org/10.1108/BIJ-05-2016-0073
12.   Al-Aomar, R., and Hussain, M. “An assessment of green practices in a hotel supply chain: A study of UAE hotels.” Journal of Hospitality and Tourism Management, Vol. 32, (2017), 71–81. https://doi.org/10.1016/j.jhtm.2017.04.002
13.   Teixeira, M. S., Maran, V., de Oliveira, J. P. M., Winter, M., and Machado, A. “Situation-aware model for multi-objective decision making in ambient intelligence.” Applied Soft Computing Journal, Vol. 81, (2019), 105532. https://doi.org/10.1016/j.asoc.2019.105532
14.   Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., and Hovy, E. “Hierarchical attention networks for document classification.” In 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, (2016), 1480–1489. https://doi.org/10.18653/v1/n16-1174
15.   Jiang, J., Wu, D., Chen, Y., and Li, K. “Complex network oriented artificial bee colony algorithm for global bi-objective optimization in three-echelon supply chain.” Applied Soft Computing Journal, Vol. 76, (2019), 193–204. https://doi.org/10.1016/j.asoc.2018.12.006
16.   Hernadewita, H., and Saleh, B. I. “Identifying tools and methods for risk identification and assessment in construction supply chain.” International Journal of Engineering, Transactions A: Basics, Vol. 33, No. 7, (2020), 1311–1320. https://doi.org/10.5829/ije.2020.33.07a.18
17.   Gardas, B. B., Raut, R. D., and Narkhede, B. “Modelling the challenges to sustainability in the textile and apparel (T&A) sector: A Delphi-DEMATEL approach.” Sustainable Production and Consumption, Vol. 15, (2018), 96–108. https://doi.org/10.1016/j.spc.2018.05.001
18.   Yayla, A. Y., Oztekin, A., Gumus, A. T., and Gunasekaran, A. “A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making.” International Journal of Production Research, Vol. 53, No. 20, (2015), 6097–6113. https://doi.org/10.1080/00207543.2015.1022266
19.   Hwang, B. N., Chen, T. T., and Lin, J. T. “3PL selection criteria in integrated circuit manufacturing industry in Taiwan.” Supply Chain Management, Vol. 21, No. 1, (2016), 103–124. https://doi.org/10.1108/SCM-03-2014-0089
20.   Tajik, G., Azadnia, A. H., Ma’aram, A. B., and Hassan, S. A. H. S. “A hybrid fuzzy MCDM approach for sustainable third-party reverse logistics provider selection.” In Advanced Materials Research (Vol. 845), (2014), 521–526. https://doi.org/10.4028/www.scientific.net/AMR.845.521
21.   Datta, S., Samantra, C., Mahapatra, S. S., Mandal, G., and Majumdar, G. “Appraisement and selection of third party logistics service providers in fuzzy environment.” Benchmarking, Vol. 20, No. 4, (2013), 537–548. https://doi.org/10.1108/BIJ-11-2011-0087
22.   Prakash, C., and Barua, M. K. “A combined MCDM approach for evaluation and selection of third-party reverse logistics partner for Indian electronics industry.” Sustainable Production and Consumption, Vol. 7, (2016), 66–78. https://doi.org/10.1016/j.spc.2016.04.001
23.   Govindan, K., KadziƄski, M., Ehling, R., and Miebs, G. “Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA.” Omega (United Kingdom), Vol. 85, (2019), 1–15. https://doi.org/10.1016/j.omega.2018.05.007
24.   Deng, X., Hu, Y., Deng, Y., and Mahadevan, S. “Supplier selection using AHP methodology extended by D numbers.” Expert Systems with Applications, Vol. 41, No. 1, (2014), 156–167. https://doi.org/10.1016/j.eswa.2013.07.018
25.   Aslani, B., Rabiee, M., and Tavana, M. “An integrated information fusion and grey multi-criteria decision-making framework for sustainable supplier selection.” International Journal of Systems Science: Operations and Logistics, (2020). https://doi.org/10.1080/23302674.2020.1776414
26.   Raut, R., Kharat, M., Kamble, S., and Kumar, C. S. “Sustainable evaluation and selection of potential third-party logistics (3PL) providers: An integrated MCDM approach.” Benchmarking, Vol. 25, No. 1, (2018), 76–97. https://doi.org/10.1108/BIJ-05-2016-0065
27.   Jung, H. “Evaluation of Third Party Logistics Providers Considering Social Sustainability.” Sustainability, Vol. 9, No. 777, (2017), 1–18. https://doi.org/10.3390/su9050777
28.   Choudhury, N., Raut, R. D., Gardas, B. B., Kharat, M. G., and Ichake, S. “Evaluation and selection of third party logistics services providers using data envelopment analysis: a sustainable approach.” International Journal of Business Excellence, Vol. 14, No. 4, (2018), 427–453. Retrieved from https://ideas.repec.org/a/ids/ijbexc/v14y2018i4p427-453.html
29.   Zarbakhshnia, N., Wu, Y., Govindan, K., and Soleimani, H. “A novel hybrid multiple attribute decision-making approach for outsourcing sustainable reverse logistics.” Journal of Cleaner Production, Vol. 242, (2020), 118461. https://doi.org/10.1016/j.jclepro.2019.118461
30.   Falsini, D., Fondi, F., and Schiraldi, M. M. “A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration.” International Journal of Production Research, Vol. 50, No. 17, (2012), 4822–4829. https://doi.org/10.1080/00207543.2012.657969
31.   Zhang, G., Shang, J., and Li, W. “An information granulation entropy-based model for third-party logistics providers evaluation.” International Journal of Production Research, Vol. 50, No. 1, (2012), 177–190. https://doi.org/10.1080/00207543.2011.571453
32.   Xiao, F. “A Multiple-Criteria Decision-Making Method Based on D Numbers and Belief Entropy.” International Journal of Fuzzy Systems, Vol. 21, No. 4, (2019), 1144–1153. https://doi.org/10.1007/s40815-019-00620-2
33.   Huang, X., Wang, N., and Wei, D. “Investment decision using D numbers.” In Proceedings of the 28th Chinese Control and Decision Conference, (2016), 4164–4167. https://doi.org/10.1109/CCDC.2016.7531712
34.   Deng, X., and Deng, Y. “D-AHP method with different credibility of information.” Soft Computing, Vol. 23, No. 2, (2019), 683–691. https://doi.org/10.1007/s00500-017-2993-9
35.   Ghayoomi, M., Abooei, M. H., Vahdatzad, M. A., and Ebrahimi, A. “Designing a model for creation of export consortiain business cluster.” International Journal of Engineering, Transactions C: Aspects, Vol. 33, No. 3, (2020), 459–467. https://doi.org/10.5829/ije.2020.33.03c.10
36.   Deng, X., and Jiang, W. “Evaluating Green Supply Chain Management Practices Under Fuzzy Environment: A Novel Method Based on D Number Theory.” International Journal of Fuzzy Systems, Vol. 21, No. 5, (2019), 1389–1402. https://doi.org/10.1007/s40815-019-00639-5
37.   Zhou, X., Deng, X., Deng, Y., and Mahadevan, S. “Dependence assessment in human reliability analysis based on D numbers and AHP.” Nuclear Engineering and Design, Vol. 313, (2017), 243–252. https://doi.org/10.1016/j.nucengdes.2016.12.001
38.   Stopka, O. “Draft to implement a logistics information system for corporate management using multi-criteria decision making methods.” Transport Economics and Logistics, Vol. 82, (2020), 43–56. https://doi.org/10.26881/etil.2019.82.04
39.   Gao, T. G., Huang, M., Wang, Q., and Wang, X. W. “Dynamic organization model of automated negotiation for 3PL providers selection.” Information Sciences, Vol. 531, (2020), 139–158. https://doi.org/10.1016/j.ins.2020.03.086
40.   Bask, A. H. “Relationships among TPL providers and members of supply chains – a strategic perspective.” Journal of Business & Industrial Marketing, Vol. 16, No. 6, (2001), 470-486. https://doi.org/10.1108/EUM0000000006021
41.   Su, X., Mahadevan, S., Xu, P., and Deng, Y. “Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP.” Risk Analysis, Vol. 35, No. 7, (2015), 1296–1316. https://doi.org/10.1111/risa.12347