Modelling of performance evaluation for last mile delivery: fuzzy AHP approach

With the rapid growth of retail and e-commerce, increasing urbanisation, evolving consumer behaviour, and a shared focus on sustainability, academic and industrial interest in last-mile logistics has surged significantly. Heightened global competition has further driven researchers and practitioners to design and implement innovative frameworks and models to enhance lastmile delivery. This paper highlights that the existing literature encompasses a wide range of factors and viewpoints, which can be broadly categorised into areas such as emerging technologies, operational optimisation, delivery chain structures, performance metrics, and geographical coverage. Among various multi-criteria decision-making (MCDM) approaches, this study employs the fuzzy analytical hierarchy process (FAHP), based on defined criteria and performance indicators. The research not only identifies key performance indicators (KPIs) within the downstream supply chain but also reveals inefficiencies and bottlenecks in the delivery flow. This technique is used to discover supply networks for warehouses. It is used to decide the comparative importance weightings or significance of various supply networks so that warehouses benefit most earnings and offer their customers great choice alternatives. The evaluation is based on three main criteria and 12 subcriteria, selected to assess and rank the factors influencing last-mile delivery performance. The findings underscore the critical importance of focusing on process management, environmental cost reduction, and customer satisfaction. This research paper is to evaluate and rank the factors influencing the performance of last mile practices also provided the industrialist and policy makers with sufficient information about the numerous factors influencing their last-mile performance.