Abstract
The pace of urban life caused a shift in shopping habits of citizens. As e-commerce rise in popularity, increasingly more packages are transferred daily. Optimization problems, urban challenges, technological advancements, and shift in citizen perception regarding last mile logistics (LML), which involves the delivery to the end customer, gained pivotal importance in the recent years. This study aims to propose a systematic evaluation of in-city logistics alternatives. As the evaluation of logistics alternatives is conducted under citizen requirements, multi-criteria decision-making (MCDM) framework is suitable to employ for this problem. For this aim, a two phased Bayesian best-worst method is used after decision criteria and in-city logistics alternatives have been identified. Firstly, best-worst method is applied to obtain the criteria weight. To obtain the ranking of the LML alternatives, best-worst comparisons of the in-city logistics alternatives are performed regarding each criterion. The evaluation of the alternatives is then aggregated to achieve the final ranking of the alternatives.