Lojistik 4.0 Hizmet Sağlayıcı Alternatiflerinin CRITIC tabanlı WASPAS Yöntemi ile Analizi

Year 2025, Issue: PRODUCTIVITY FOR LOGISTICS, 77 - 88, 03.02.2025

Muhammet Enes Akpınar

https://doi.org/10.51551/verimlilik.1523739

Abstract

Amaç: Bu çalışmanın amacı, dijital dönüşüm ve Endüstri 4.0 teknolojileriyle şekillenen Lojistik 4.0 kavramı çerçevesinde, lojistik hizmet sağlayıcılarının değerlendirilmesi ve en uygun hizmet sağlayıcının belirlenmesidir. Lojistik 4.0, akıllı sistemler ve büyük veri analitiği gibi yenilikçi teknolojileri kullanarak lojistik süreçleri optimize etmeyi hedefler. Bu bağlamda, doğru hizmet sağlayıcıyı seçmek, işletmeler için stratejik bir öneme sahiptir. Çalışma, işletmelerin bu karmaşık süreçte doğru kararlar almasına yardımcı olmayı amaçlamaktadır.
Yöntem: CRITIC (Criteria Importance Through Intercriteria Correlation) tabanlı WASPAS (Weighted Aggregated Sum Product Assessment) yöntemi kullanılmıştır. CRITIC yöntemi ile kriterlerin objektif ağırlıkları belirlenmiş, WASPAS yöntemi ise bu ağırlıkları kullanarak alternatiflerin genel performans skorlarını hesaplamıştır.
Bulgular: Çalışma sonuçları, işletmelerin Lojistik 4.0 hizmet sağlayıcılarını seçerken dikkat etmeleri gereken önemli kriterleri ve en iyi performans gösteren hizmet sağlayıcıları ortaya koymuştur.
Özgünlük: Bu çalışma, CRITIC ve WASPAS yöntemlerinin birlikte kullanımının, lojistik sektöründe hizmet sağlayıcı seçiminde sağladığı avantajları ve yöntemlerin etkinliğini vurgulamaktadır. Ayrıca, lojistik sektöründe Lojistik 4.0 hizmet sağlayıcılarının seçimi konusunda literatüre katkı sağlamaktadır.

Keywords

Lojistik 4.0, Çok Kriterli Karar Verme, CRITIC

Analysis of Logistics 4.0 Service Provider Alternatives with CRITIC-Based WASPAS Method

Abstract

Purpose: This study aims to evaluate and identify the most suitable logistics service providers within the framework of Logistics 4.0, shaped by digital transformation and Industry 4.0 technologies. Logistics 4.0 seeks to optimize logistics processes using innovative technologies such as smart systems and big data analytics. In this context, selecting the right service provider is of strategic importance for businesses. This study intends to assist companies in making accurate decisions in this complex process.
Method: The CRITIC (Criteria Importance Through Intercriteria Correlation) based WASPAS (Weighted Aggregated Sum Product Assessment) method was employed. The CRITIC method was used to determine the objective weights of the criteria, while the WASPAS method utilized these weights to calculate the overall performance scores of the alternatives.
Findings: The results of the study reveal the key criteria that businesses should consider when selecting Logistics 4.0 service providers and identifying the top-performing service providers.
Originality: This study highlights the advantages and effectiveness of using the combined CRITIC and WASPAS methods in the selection of service providers in the logistics sector. Additionally, it contributes to the literature on the selection of Logistics 4.0 service providers.

Keywords

Logistics 4.0, Multi-Criteria Decision Making, CRITIC, WASPAS

References

• Abdelhafeez, A., Khalil, N. A., Eassa, M., & Elkholy, M. (2024). “Selection Optimal Livestock Location under Multi-Criteria Decision Making Fuzzy Framework”. Precision Livestock, 1, 58-65.
• Abouhawwash, M. and Jameel, M. (2023). “Evaluation Factors of Solar Power Plants to Reduce Cost Under Neutrosophic Multi-Criteria Decision Making Model”, Sustainable Management Journal, 2(3), 101-114.
• Abualkishik, A. and Almajed, R. (2023). “WASPAS Multi-Criteria Decision-Making Method for Assessment Effectiveness and Performance Intelligent Transportation Systems Alternatives”, Financial Technology & Innovation, 3(1), 1-12.
• Agyabeng-Mensah, Y., Ahenkorah, E., Afum, E., Owusu, L., Agyabeng, C. and Baah, C. (2020). “The Influence of Logistics Outsourcing, Information Technology, and Innovation Capabilities on Supply Chain Sustainability”, Journal of Cleaner Production, 258, 120808. https://doi.org/10.1016/j.jclepro.2020.120808
• Ahmad, A. and Ozcek, M. (2023). “Multi-Criteria Decision-Making Methodology for Sustainable Crop Selection”, International Journal of Artificial Intelligence and Computing, 6(1), 1-15.
• Ahmad, U., Khan, A. and Saeid, A. (2023). “Integrated Multi-Criteria Group Decision-Making Methods Based on Q-Rung Picture Fuzzy Sets for the Identification of Occupational Hazards”, Applied Soft Computing, 123, 105591.
• Akmermer, B., & Çelik, P. (2021). “Contribution of fishery and aquaculture products to Turkish foreign trade: An evaluation by a hybrid multi-criteria decision-making method”. Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS)/Su Ürünleri Dergisi, 38(3).
• Akpınar, M. E. (2021). “Third-party logistics (3PL) provider selection using hybrid model of SWARA and WASPAS”. International Journal of Pure and Applied Sciences, 7(3), 371-382.
• Alharbi, A.H., Jabali, H.M., Rajan, P. and Salamai, A. (2024). “Evaluation Challenges of Leadership Management in the Energy Sector using Multi-Criteria Decision Making Approach”, Management Studies, 4(2), 21-30.
• Al-Hchaimi, A.A.J., Sulaiman, N.B., Mustafa, M.A.B, Mohtar, M.N.B, Hassan, S.L.B.M. and Muhsen, Y.R. (2022). “Evaluation Approach for Efficient Countermeasure Techniques Against Denial-of-Service Attack on MPSoC- Based IoT Using Multi-Criteria Decision-Making”, IEEE Access, 10, 114569-114585. https://doi.org/10.1109/ACCESS.2022.3232395
• Arisantoso, A., Somaida, M.H., Sanwasih, M. and Shalahudin, M.I. (2023). “Multi-Criteria Decision Making Using the WASPAS Method in Webcam Selection Decision Support Systems”, Indonesian Journal of Computing Science, 7(1), 1-11.
• Aytekin, A., Görçün, Ö.F., Ecer, F., Pamucar, D. and Karamaşa, Ç. (2023). “Evaluation of the Pharmaceutical Distribution and Warehousing Companies through An Integrated Fermatean Fuzzy Entropy-WASPAS Approach”, Kybernetes, 52(11), 5561-5592.
• Barbara, F., dos Santos, M., Silva, A.S., Moreira, M., Lopes Fávero, L.P., Pereira Júnior, E.L., Carvalho, W.A., Muradas, F., Pereira, D.A. de M. and Portella, A.G. (2023). “Interactive Internet Framework Proposal of WASPAS Method: A Computational Contribution for Decision-Making Analysis”, Mathematics, 11(15), 3375.
• Barreto, L., Amaral, A. and Pereira, T. (2017). “Industry 4.0 Implications in Logistics: An Overview”, Procedia Manufacturing, 13, 1245-1252.
• Büyüközkan, G. and Göçer, F. (2018). “Digital Supply Chain: Literature Review and A Proposed Framework for Future Research”, Computers in Industry, 97, 157-177. https://doi.org/10.1016/j.compind.2018.02.010
• Choi, T.M., Chan, H.K. and Yue, X. (2019). “Recent Development in Big Data Analytics for Business Operations and Risk Management”, IEEE Transactions on Cybernetics, 49(1), 36-45.
• de Oliveira, U.R. and Handfield, R. (2019). “Analytical Models for Assessing Green Supply Chain Practices in the Brazilian Automotive Industry”, Resources, Conservation and Recycling, 145, 269-278. https://doi.org/10.1016/j.resconrec.2019.02.031
• Diakoulaki, D., Mavrotas, G. and Papayannakis, L. (1995). “Determining Objective Weights in Multiple Criteria Problems: The CRITIC Method”, Computers & Operations Research, 22(7), 763-770. https://doi.org/10.1016/0305-0548(94)00059-H
• Do, T. (2021). “The Combination of Taguchi – Entropy – WASPAS - PIV Methods for Multi-Criteria Decision Making When External Cylindrical Grinding of 65G Steel”, Journal of Manufacturing Engineering, 14, 1-12.
• Fottler, M., Ford, E. and Braunscheidel, M. (2020). “Healthcare Operations Management: A Systems Perspective”, Routledge. https://doi.org/10.4324/9781003046778
• Gökkuş, Z., Şentürk, S., & Alatürk, F. (2023). “Ranking Çanakkale Districts in terms of rangeland quality with multi-criteria decision making methods”. Türk Tarım ve Doğa Bilimleri Dergisi, 10(3), 605-614.
• Govindan, K., Soleimani, H. and Kannan, D. (2018). “Reverse Logistics and Closed-Loop Supply Chain: A Comprehensive Review to Explore the Future”, European Journal of Operational Research, 240(3), 603-626.
• Günay, F. and Ecer, F. (2022). “A Comparative Analysis of the Real Sector in Turkey from the Economic and Financial Perspectives with the CRITIC-MAIRCA Method”, Ekonomi Politika ve Finans Araştırmaları Dergisi, 7(1), 186-219.
• Handayani, N., Heriyani, N., Septian, F. and Alexander, A.D. (2023). “Multi-Criteria Decision Making Using the WASPAS Method for Online English Course Selection”, Teknoinfo, 17(1), 1-10.
• Hassan, I., Alhamrouni, I. and Azhan, N.H. (2023). “A CRITIC–TOPSIS Multi-Criteria Decision-Making Approach for Optimum Site Selection for Solar PV Farm”, Energies, 16(10), 4245.
• Heidary Dahooie, J., Husseinzadeh Kashan, A., Shoaei Naeini, Z., Vanaki, A.S., Zavadskas, E.K. and Turskis, Z. (2022). “A Hybrid Multi-Criteria-Decision-Making Aggregation Method and Geographic Information System for Selecting Optimal Solar Power Plants in Iran”. Energies, 15(8), 2801.
• Hofmann, E. and Rüsch, M. (2017). “Industry 4.0 and the Current Status as well as Future Prospects on Logistics”, Computers in Industry, 89, 23-34.
• Ivanov, D., Dolgui, A. and Sokolov, B. (2019). “The Impact of Digital Technology and Industry 4.0 on the Ripple Effect and Supply Chain Risk Analytics”, International Journal of Production Research, 57(3), 829-846.
• Kannan, D., Govindan, K. and Rajendran, S. (2020). “Fuzzy AHP Integrated with Fuzzy TOPSIS for Analyzing Logistics Service Provider Selection Criteria”, Journal of Cleaner Production, 106, 256-267. https://doi.org/10.1016/j.jclepro.2014.11.053
• Karaca, C. and Ulutaş, A. (2018). “Entropi ve WASPAS Yöntemleri Kullanılarak Türkiye Için Uygun Yenilenebilir Enerji Kaynağının Seçimi”, Ege Academic Review, 18(3), 483-494.
• Khalilzadeh, M., Banihashemi, S.A. and Božanić, D. (2024). “A Step-by-Step Hybrid Approach Based on Multi-Criteria Decision-Making Methods and A Bi-Objective Optimization Model to Project Risk Management”, Decision Making in Manufacturing and Services, 7(1), 1-15.
• Krishankumar, R., Mishra, A.R., Rani, P., Ecer, F. and Ravichandran, K.S. (2023). “Assessment of Zero-Carbon Measures for Sustainable Transportation in Smart Cities: A CRITIC-MARCOS Framework Based on Q-Rung Fuzzy Preferences”, IEEE Internet of Things Journal, 10(21), 18651-1866. https://doi.org/10.1109/JIOT.2023.3293513
• Kumar, R., Goel, P., Zavadskas, E., Stević, Ž. and Vujović, V. (2022). “A New Joint Strategy for Multi-Criteria Decision-Making: A Case Study for Prioritizing Solid-State Drive”, International Journal of Computers Communications & Control, 17(6), 5010.
• Lai, H. and Liao, H. (2021). “A Multi-Criteria Decision Making Method Based on DNMA and CRITIC with Linguistic D Numbers for Blockchain Platform Evaluation”, Engineering Applications of Artificial Intelligence, 95, 104200.
• Mayatopani, H. (2023). “Multi-Criteria Decision Making Using Weighted Aggregated Sum Product Assessment in Corn Seed Selection System”, Cereal International, 15, 21-31.
• Mohamed, M., Ayman, S. and Sleem, A. (2024). “Valuation of Internet of Energy (IoE) Platforms in Smart Cities: A Hybrid Multi-Criteria Decision Making Approach”, Plant Cell Biotechnology and Molecular Biology, 25(3), 253-264.
• Nabavi, S., Wang, Z. and Rangaiah, G.P. (2024). “Sensitivity Assessment of Multi-Criteria Decision-Making Methods in Chemical Engineering Optimization Applications”, arXiv preprint.
• Narayanamoorthy, S., Brainy, J.V., Manirathinam, T., Kalaiselvan, S., Kureethara, J.V. and Kang, D. (2021). “An Adoptable Multi-Criteria Decision-Making Analysis to Select a Best Hair Mask Product-Extended Weighted Aggregated Sum Product Assessment Method”, Fuzzy Information and Engineering, 7(1), 1-10.
• Özekenci, E.K. (2023). “Evaluation of Export Performances of Metropolitans in Turkey Based on Integrated Multi-Criteria Decision-Making Methods”, Dicle University Journal of Economics and Administrative Sciences, 14(1), 59-74.
• Pala, F. (2023). “Comparison of the Companies Operated for Technology and Information Sector in BIST by Multi-Criteria Decision Making Method and Financial Performance Measurements”, Financial Studies, 27(1), 117-130.
• Rastpour, E., Kayvanfar, V. and Rafiee, M. (2022). Multi-Criteria Decision-Making Methods for the Evaluating of A Real Green Supply Chain in Companies with Fast-Moving Consumer Goods”, International Journal of Production Research, 1, 1-14.
• Saarikko, T., Westergren, U.H. and Blomquist, T. (2020). “Digital Transformation: Five Recommendations for the Digitally Conscious Firm”, Business Horizons, 63(6), 825-839. https://doi.org/10.1016/j.bushor.2020.07.005
• Sarucan, A., Baysal, M.E. and Engin, O. (2024). “Ranking of the Member Countries in the Black Sea Economic Cooperation Organization Using Multi-Criteria Decision-Making Methods”, Journal of Sustainable Development, 19(1), 101-113.
• Shao, C., Wei, B., Liu, W., Yang, Y., Zhao, Y. and Wu, Z. (2023). “Multi-Dimensional Value Evaluation of Energy Storage Systems in New Power System Based on Multi-Criteria Decision-Making”, Processes, 11(5), 1565.
• Sharma, M., Luthra, S., Joshi, S., & Kumar, A. (2022). “Developing a framework for enhancing survivability of sustainable supply chains during and post-COVID-19 pandemic”. International Journal of Logistics Research and Applications, 25(4-5), 433-453.
• Taletović, M. (2023). “Application of Multi-Criteria Decision-Making Methods in Warehouse: A Brief Review”, Studies in Economics and Management, 11, 31-45.
• Ulutaş, A. and Karaköy, Ç. (2019). “CRITIC ve ROV Yöntemleri Ile Bir Kargo Firmasının 2011-2017 Yılları Sırasındaki Performansının Analiz Edilmesi”, MANAS Sosyal Araştırmalar Dergisi, 8(1), 223-230.
• Wang, G., Gunasekaran, A., Ngai, E.W. and Papadopoulos, T. (2020). “Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for Research and Applications”, International Journal of Production Economics, 176, 98-110.
• Yazdani, M., Chatterjee, P., Zavadskas, E.K. and Streimikiene, D. (2019). “A Novel Integrated Decision-Making Approach for the Evaluation and Selection of Sustainable Suppliers in the Power Industry”, Sustainability, 10(1), 1-19. https://doi.org/10.3390/su10010015
• Yilmaz, K. and Burdurlu, E. (2023). “Selection of Wooden Furniture Joints with Multi-Criteria Decision-Making Techniques”, International Journal of Computer Integrated Manufacturing, 36(8), 842-856.
• Zaher, M. A., & Eldakhly, N. M. (2023). “An Integrated Framework for Dynamic Resource Allocation in Multi-project Environment”. Full Length Article, 10(1), 08-8.
• Zavadskas, E.K. and Turskis, Z. (2012). “A New Additive Ratio Assessment (ARAS) Method in Multicriteria Decision-Making”, Technological and Economic Development of Economy, 16(2), 159-172.
• Zavadskas, E.K., Turskis, Z. and Kildienė, S. (2012). “State of Art Surveys of Overviews on MCDM/MADM Methods”, Technological and Economic Development of Economy, 18(4), 672-695.
• Zhang, X., Lv, M. and Yuan, X. (2023). “Research on Cloud-CRITIC-PDR Method for Hybrid Multi-Criteria Decision Making”, Journal of Intelligent & Fuzzy Systems, 45, 5067-5078.