En Uygun Tersine Lojistik Hizmet Sağlayıcısının Bulanık Grup Karar Verme Yaklaşımı Altında Belirlenmesi

Günümüz pazar koşullarında işletmeler lojistik operasyonlarını maliyet ve rekabet avantajı sağlayacak etkin bir stratejiyle sürdürmek zorundadır. Müşterilerden gelen fiyat baskıları ve özellikle politik, ekonomik ve çevresel hassasiyetler gereği, ürün geri dönüşüm süreçleri -yani ürünün geri kazanılarak yeniden değerlendirilmesi- tersine lojistik (TL) uygulamalarını gerektirmektedir. İşletmeler için, TL yönetiminde genellikle özel bilgi sistemlerine sahip bir altyapı ve iadelerin işlenmesi için özel ekipmanlar gereklidir. Bu nedenle çoğu işletme sınırlı kaynakları ve teknik yeterlilikleri nedeniyle TL faaliyetlerini üçüncü parti TL sağlayıcılarına (3PTLS) devretmektedir. Uygun 3PTLS seçim süreci işletmelerin ekonomik karlılığına ve uzun vadeli gelişimine katkı sunması nedeniyle stratejik olarak önemli bir karardır. 3PTLS seçim kararı, çok sayıda belirsizlik içermesi ve karmaşık doğası gereği çok kriterli karar verme (ÇKKV) problemi olarak ele alınmaktadır. Bu çalışmada, en iyi 3PTLS seçimi için insan düşüncelerindeki belirsizlik ve karmaşıklığı daha iyi yansıtmak amacıyla Pisagor bulanık kümelere dayalı bir grup karar verme modeli olarak Pisagor bulanık TOPSIS yöntemi kullanılarak modellenmiştir. Modelin uygulanabilirliği, bir pil üretim şirketinden alınan verilere dayanan deneysel bir çalışma ile gösterilmiştir. Elde edilen sonuçlar diğer karar verme yöntemleriyle (bulanık TOPSIS, bulanık COPRAS ve klasik TOPSIS) karşılaştırılmış ve çözüm üstünlükleri sunulmuştur. Ayrıca önerilen modelin kararlılığını ve uygulanabilirliğini değerlendirmek için duyarlılık analizi yapılmıştır.

Anahtar Kelimeler:

Tersine Lojistik, Çok Kriterli Karar Verme, Grup Karar Verme, Pisagor Bulanık TOPSIS, Bulanık COPRAS

Selection of the Appropriate Reverse Logistics Provider Under Fuzzy Group Decision Making Approach

In today's market conditions, companies have to maintain their logistics operations with an effective strategy that will provide cost and competitive advantage. Pricing pressures from customers, and specifically due to political, economic and environmental sensitivities, require reverse logistics (RL) applications in product recycling processes, that is, for recycling and re-evaluation of the product. Companies usually require an infrastructure with special information systems and particular equipment for processing returns in RL management. For this reason, most companies transfer their RL activities to third-party RL providers (3PRLP) due to their limited resources and technical capabilities. The appropriate 3PTLS selection is a strategically important decision because of its contribution to the economic profitability and long-term development of businesses. 3PRLP selection decision is considered as a multi-criteria decision-making (MCDM) problem due to the high number of uncertainties and complicated natures. In this study, a multi-criteria group decision-making model based on Pythagorean fuzzy sets was modeled using the Pythagorean fuzzy TOPSIS method to better reflect the uncertainty and complexity in human views/opinions for the best 3PRLP selection. The applicability of the model has been demonstrated and tested by an experimental study based on data from a battery manufacturing company. The obtained results were compared with other decision-making methods (classical TOPSIS, fuzzy TOPSIS and fuzzy COPRAS) and solution advantages were presented in the study. In addition, sensitivity analysis was applied to evaluate the stability and applicability of the proposed model.

Keywords:

Reverse Logistic, Multi-Criteria Decision Making, Group Decision Making, Pythagorean Fuzzy TOPSIS, Fuzzy COPRAS,

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