Modeling Retail Supply Chain Efficiency: Exploration and Comparative Analysis of Different Approaches

Abstract

Retail supply chains are key on any market. Their significance has long been recognized in the literature and in practice. Various factors such as pandemics, economic crises, wars, and natural disasters have further increased interest in this area. However, the most recent research has focused more on resilience, sustainability, energy consumption, and a circular economy, while the efficiency of logistics processes has been almost completely overlooked. Logistics process efficiency in retail supply chain is a fundamental principle without which all mentioned performances cannot have desired values. This gap is precisely the main motivation of this research. In this paper, research models in literature are presented which can be used, with some modifications, to measure the efficiency of the retail supply chain. The models were based on the data envelopment analysis (DEA) approach. Four main groups were identified: standard DEA models, efficiency decomposition models, network models, and game-theory-based models. In the second part of the paper, various approaches were tested on a real example of a trading company operating in Serbia. Seven supply chains were observed, each consisting of a distribution center (DC) and retail store (RS). Variables used were the number of pallet places, logistics costs, number of deliveries, accuracy of deliveries, and turnover. The results showed the advantages and disadvantages of different approaches in real examples. The main contributions of this paper lie in unique approaches to measuring the efficiency of the retail supply chain. The paper creates an excellent foundation for future research and measurements on real systems, which is equally useful for researchers and industry experts.