Ibragim Musaevich Bamatov, Anatolij Sergeevich Utyuzh, Vladimir Dmitriyevich Sekerin, Anna Evgenyevna Gorokhova, Dmitrii Anatolievich Shevchenko, Natalia Viktorovna Gayduk
Ibragim Musaevich Bamatov1*, Anatolij Sergeevich Utyuzh2, Vladimir Dmitriyevich Sekerin3, Anna Evgenyevna Gorokhova3, Dmitrii Anatolievich Shevchenko3, Natalia Viktorovna Gayduk4
1Department of Biology and Chemistry, Chechen State University, Sheripova Str., 32, Grozny, 364024, Russia.
2I.M. Sechenov First Moscow State Medical University Department of Prosthetic Dentistry, Trubetskayast., 8-2, Moscow, 119991, Russian Federation.
3Moscow Polytechnic University, Bolshaya Semenovskaya St., 38, Moscow, 107023, Russian Federation.
4Kuban State Agrarian University, Kalinina Str., 13, Krasnodar, 350044, Russian Federation.
Volume - 13,
Issue - 10,
Year - 2020
The new realities, such as increased regulatory requirements, introduction of new gene and cellular therapies, and expectations of such therapies to be more affordable in healthcare facilities, require building a cold chain, which is very flexible and more reliable. Finding the most suitable provider of logistics services is an important part of building a cold chain for the pharmaceutical products supply. Selecting a logistics service provider is a decision-making process based on a few criteria and associated with the optimization of conflicting goals, such as quality, cost, and delivery time. A system to support decision on selecting a logistics service provider is suggested in this article, based on the method of analytical hierarchy process (AHP), which is widely used to solve multicriteria tasks. A case study is conducted by the example of a pharmaceutical industry manufacturer in order to validate the choice of the AHP model and to justify the conceptual design of the system to support decision on selecting a logistics service provider.
Cite this article:
Ibragim Musaevich Bamatov, Anatolij Sergeevich Utyuzh, Vladimir Dmitriyevich Sekerin, Anna Evgenyevna Gorokhova, Dmitrii Anatolievich Shevchenko, Natalia Viktorovna Gayduk. Selecting a provider as the most important step in building a cold chain in Pharmaceutical Logistics. Research J. Pharm. and Tech. 2020; 13(10):4641-4647. doi: 10.5958/0974-360X.2020.00817.3
Ibragim Musaevich Bamatov, Anatolij Sergeevich Utyuzh, Vladimir Dmitriyevich Sekerin, Anna Evgenyevna Gorokhova, Dmitrii Anatolievich Shevchenko, Natalia Viktorovna Gayduk. Selecting a provider as the most important step in building a cold chain in Pharmaceutical Logistics. Research J. Pharm. and Tech. 2020; 13(10):4641-4647. doi: 10.5958/0974-360X.2020.00817.3 Available on: https://rjptonline.org/AbstractView.aspx?PID=2020-13-10-20
1. Biopharma Cold Chain Sourcebook. 2018. Retrieved July 12, 2019 from https://pharmaceuticalcommerce.com/.
2. Rodrigues AC, Martins RS, Wanke PF and Siegler J. Efficiency of specialized 3PL providers in an emerging economy. International Journal of Production Economics. 2018; 205: 163-178.
3. Sremac S, Stević Ž, Pamučar D, Arsić M and Matić B. Evaluation of a third-party logistics (3PL) provider using a rough SWARA-WASPAS model based on a new rough dombi aggregator. Symmetry. 2018; 10(8): 305.
4. Manzini R, Pareschi A and Persona A. Logistics outsourcing: An examination of third-party providers. International Journal of Logistics Systems and Management. 2007; 3(2): 135-157.
5. Arif J and Jawab F. Outsourcing of Logistics' Activities: Impact Analysis on Logistics Service Performance. In International Colloquium on Logistics and Supply Chain Management Logistiqua 2018. Tangier: FST.2018; pp. 88-92.
6. Marasco A. Third-party logistics: A literature review. International Journal of Production Economics. 2008; 113(1): 127-147.
7. Shi Y, Yang Z, Yan H and Tian X. Delivery efficiency and supplier performance evaluation in China’s E-retailing industry. Journal of Systems Science and Complexity. 2017; 30(2): 392-410.
8. Marchet G, Melacini M, Sassi C and Tappia E. Assessing efficiency and innovation in the 3PL industry: an empirical analysis. International Journal of Logistics Research and Applications. 2017; 20(1): 53-72.
9. Sahay BS and Mohan R. Managing 3PL relationships. International Journal of Integrated Supply Management. 2006; 2(1-2): 69-90.
10. Jeffers PI. Embracing sustainability: Information technology and the strategic leveraging of operations in third-party logistics. International Journal of Operations and Production Management. 2010; 30(3): 260-287.
11. Osorio Gómez JC, Manotas Duque DF, Rivera L and García-Alcaraz JL. Decision support system for operational risk management in supply chain with 3PL providers. Intelligent Systems Reference Library.2017; 120: 205-222.
12. Raut R, Kharat M, Kamble S and Kumar CS. Sustainable evaluation and selection of potential third-party logistics (3PL) providers: An integrated MCDM approach. Benchmarking.2018; 25(1): 76-97.
13. Bianchini A. 3PL provider selection by AHP and TOPSIS methodology. Benchmarking. 2018; 25(1): 235-252.
14. Raut RD, Kharat MG, Kamble SS, Kamble SJ and Desai R. Evaluation and selection of third-party logistics providers using an integrated multi-criteria decision-making approach. International Journal of Services and Operations Management.2018;29(3): 373-392.
15. Keshavarz Ghorabaee M, Amiri M, Kazimieras Zavadskas E and Antuchevičienė J. Assessment of third-party logistics providers using a CRITIC–WASPAS approach with interval type-2 fuzzy sets. Transport. 2017; 32(1): 66-78.
16. Omrani H, Hushyar I, Zolmabadi SM and Asl AJ. A multi-objective programming model for selection third-party logistics companies and suppliers in a closed-loop supply chain. International Journal of Industrial and Systems Engineering. 2018; 30(4): 486-511.
17. Raut RD, Kamble SS, Kharat MG, Joshi H, Singhal C and Kamble SJ. A hybrid approach using data envelopment analysis and artificial neural network for optimising 3PL supplier selection. International Journal of Logistics Systems and Management. 2017; 26(2): 203-223.
18. Quariguasi FrotaNeto J, Bloemhof-Ruwaard JM, van Nunen JAEE and van HeckE. Designing and evaluating sustainable logistics networks. International Journal of Production Economics. 2008; 111(2): 195-208.
19. Borade AB, Kannan G and Bansod SV. Analytical hierarchy process-based framework for VMI adoption. International Journal of Production Research. 2013; 51(4): 963-978.
20. Grewal CS, Sareen KK and Gill S. A multicriteria logistics-outsourcing decision making using the analytic hierarchy process. International Journal of Services, Technology and Management. 2008; 9(1): 1-13.
21. Percin S. Evaluation of third-party logistics (3PL) providers by using a two-phase AHP and TOPSIS methodology. Benchmarking. 2009; 16(5): 588-604.
22. Haq AN and Kannan G. Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model. International Journal of Advanced Manufacturing Technology. 2006; 29(7-8): 826-835.
23. Daim TU, Udbye A and Balasubramanian A. Use of analytic hierarchy process (AHP) for selection of 3PL providers. Journal of Manufacturing Technology Management. 2013; 24(1): 28-51.
24. Mathiyazhagan K and Bhalotia A. Assessment of criteria for the selection of third-party logistics provider: A case from India. International Journal of Logistics Systems and Management. 2018; 30(2): 268-282.
25. Aguezzoul A. Third-party logistics selection problem: A literature review on criteria and methods. Omega.2014; 49: 69-78.
26. Qureshi MN, Kumar D and Kumar P. An integrated model to identify and classify the key criteria and their role in the assessment of 3PL services providers. Asia Pacific Journal of Marketing and Logistics.2008; 20(2): 227-249.