Abstract
In large urban agglomerations, various logistical problems arise due to high population density and deficient transport infrastructure. City logistics involves the efficient distribution of freight transport in urban areas and approaches to mitigate environmental impacts and traffic congestion. This paper aims to use a two-step cluster analytic approach to segmentation of EU27 capital cities based on their city logistics performance. To obtain primary outcomes, the log-likelihood measure in SPSS Statistics was used. The results can be used to identify the development and implementation of logistics measures in capitals across the EU. In addition to clustering, the statistical analysis evaluates the position of investigated cities concerning traffic congestions, and from an environmental point of view, the carbon dioxide produced from transport. The scrutiny delivers practical outlooks on how clustering can be undertaken and proves how the clusters can be used to plan city logistics and supply chain management. Finally, the paper deals with smart city indices from the perspective of sustainable mobility and examines its correlation with city logistics.
Funder
European Regional Development Fund
University of Žilina
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development
Cited by
23 articles.
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