Hybrid Multi-Criteria Decision-Making Model for Optimal Selection of Cold Chain Logistics Service Providers
Journal Title: Journal of Organizations, Technology and Entrepreneurship - Year 2023, Vol 1, Issue 2
Abstract
In the context of the global supply chain, the selection of Cold Chain Logistics Service Providers (CCLSPs) emerges as a paramount challenge, particularly for the transportation of temperature-sensitive goods. This study introduces a structured decision-making framework, addressing the need for efficient and reliable logistics services in this sector. Central to the framework is a hybrid Multi-Criteria Decision-Making (MCDM) model, which synergizes Fuzzy FActor RElationship (Fuzzy FARE) and Fuzzy Axial Distance based Aggregated Measurement (Fuzzy ADAM). This innovative approach is aimed at refining criteria weight determination and enhancing provider ranking accuracy. Special emphasis is placed on the integration of fuzzy logic to manage the inherent uncertainties present in subjective evaluations and decision data. The investigation underscores the criticality of factors such as stringent temperature control, robust infrastructure, and adherence to regulatory standards in the selection process. An application of this methodology is demonstrated through a case study involving the ranking of ten logistics providers in South-East Europe. The study's contributions are twofold: it advances the theoretical framework of supply chain management methodologies and offers a pragmatic tool for businesses operating within temperature-sensitive logistics networks. Prospective research directions include the adaptation of this framework to various regional contexts and the incorporation of emerging technologies, ensuring the framework's applicability and relevance in the dynamic domain of cold chain logistics.
Authors and Affiliations
Mladen Krstić, Snežana Tadić
Keywords
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- EP ID EP732678
- DOI https://doi.org/10.56578/jote010201
- Views 67
- Downloads 0
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