setsci

SETSCI Conference Proceedings

2687-5527

SET Technology

10.36287/setsci.4.8.006

3f1182fa-6129-4565-811d-00a61535ec63

Third-Party Logistics Provider Selection By Using AHP and CODAS Methods

Ulutaş

Alptekin

Sivas Cumhuriyet University

23 12 2019

11 36 38

2019

SET Technology

CC BY 4.0

Companies would like to gain a competitive advantage in today's world where global competition is intense by focusing on their main activities. Therefore, most of the companies use outsourcing for their logistics activities. Third-party logistics providers are outsourcing organizations that perform some or all of the logistics activities of companies. In order for the logistics activities to continue accurately in the medium and long term, companies need to establish a strategic partnership with a good third-party logistics provider. To achieve this goal, companies should identify the best third-party logistics provider. Many factors and alternatives need to be considered in the problem of selecting third-party logistics providers. Therefore, this problem can be called a multi-criteria decision-making (MCDM) problem. In this study, third-party logistics provider selection will be made for a textile company with the Analytic Hierarchy Process (AHP) and Combinative Distance-Based Assessment (CODAS) methods. In this study, four alternatives were evaluated with respect to six criteria

Third-party logistics provider, AHP, CODAS, MCDM, Logistics

S. Sremac, Ž. Stević, D. Pamučar, M. Arsić, and B. Matić, “Evaluation of a third-party logistics (3PL) provider using a rough SWARA–WASPAS model based on a new rough dombi aggregator,” Symmetry, vol. 10, no.8, 305, 2018.

N. Zarbakhshnia, H. Soleimani, and H. Ghaderi, “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, vol. 65, pp. 307-319, 2018.

R. K. Singh, A. Gunasekaran, and P. Kumar, “Third party logistics (3PL) selection for cold chain management: a fuzzy AHP and fuzzy TOPSIS approach,” Annals of Operations Research, vol. 267, no. (1-2), pp. 531-553, 2018.

D. Pamucar, K. Chatterjee, and E. K. Zavadskas, “Assessment of third-party logistics provider using multi-criteria decision-making approach based on interval rough numbers,” Computers & Industrial Engineering, vol. 127, pp. 383-407, 2019.

K. Govindan, M. Kadziński, R. Ehling, and G. Miebs, “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, vol. 85, pp. 1-15, 2019.

E. Ayçin, “Üçüncü Parti Lojistik Hizmet Sağlayıcı Seçim Kriterlerinin Gri DEMATEL Bütünleşik Yaklaşımıyla Belirlenmesi,” Alphanumeric Journal, vol. 6, no.2, pp. 277-292, 2019.

T. L. Saaty, “A Scaling Method for Priorities in Hierarchical Structures,” Journal of Mathematical Psychology, vol. 15, pp. 234-281, 1977.

A. Özbek, and T. Eren, “Üçüncü Parti Lojistik (3PL) Firmanın Analitik Hiyerarşi Süreciyle (AHS) Belirlenmesi,” Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi, vol. 5, pp. 12-20, 2013.

T. L. Saaty, “How to Make a Decision: The Analytic Hierarchy Process,” Interfaces, vol. 24, pp.19-43, 1994.

M. Keshavarz Ghorabaee, E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, “A New Combinative Distance-Based Assessment (Codas) Method For Multi-Criteria Decision-Making,” Economic Computation & Economic Cybernetics Studies & Research, vol. 50, pp. 25-44, 2016.