Benchmarking the efficiency of distribution warehouses using a four-phase integrated PCA-DEA-improved fuzzy SWARA-CoCoSo model for sustainable distribution

Abstract

In a dynamic market marked by disruptions like pandemics and recessions, organizations face significant challenges in efficiently managing logistics processes and activities. The primary objective of this article is to propose an integrated four-phase model for assessing the efficiency of retail distribution warehouses based on principal component analysis-data envelopment analysis-improved fuzzy step-wise weight assessment ratio analysis-combined compromise solution (PCA-DEA-IMF SWARA-CoCoSo). The model provides a synergistic effect of all positive sides of the considered methods. PCA-DEA methods are used to reduce the number of variables and to identify efficient warehouses. IMF SWARA is applied to determine criteria weights, while the CoCoSo method is employed in the last phase for ranking efficient warehouses. The model incorporates 18 inputs and 3 outputs, derived from both literature and real-world systems. The proposed model identifies the most efficient warehouses, which can serve as benchmarks for improving the performance of less efficient ones. After implementing PCA-DEA, only seven warehouses were identified as efficient. Subsequently, fixed and variable costs are identified as the two most important criteria. Results of the considered case study indicate that warehouse A4 emerges as the best one, whereas A6 is the least preferred warehouse. This research offers valuable insights and practical implications for organizations operating in dynamic markets, assisting them in achieving operational excellence and improving their supply chain performance.

Keywords

• distribution
• warehouses
• efficiency
• logistics
• performance
• four-phase model
• mcdm
• retail
• 90b06
• 91b06