The paper presents a systematic quantitative and qualitative literature review and classification of the last decades resources for a comprehensive and coherent view of smart city and urban logistics research trends and challenges. The review ...

The topic of global warming is and will continue to be a crucial topic of this millennium. Freight transport, as a producer of greenhouse gas (hereinafter GHG) emissions, makes a significant contribution to the greenhouse effect. Large supply chains and large volumes of freight transport, which imply the production of significant volumes of GHG emissions, characterize the automotive industry (hereinafter AI). Thanks to these premises, it is necessary to seek and develop tools for reducing the volume of GHG emissions produced from the logistic activities of the AI, while maintaining the required level of logistic services. The assumptions for the calculation of GHG emissions from railway freight transport (hereinafter RFT) in the AI were identified through the use of semi-structured interviewing. Available railway freight GHG emission calculators were identified and analyzed from the perspective of suitability for the AI using a comparative content analysis. The main result of this manuscript is the proposal of a fully customized approach to GHG emission calculations in RFT for the AI. This approach was proposed, applied, and verified in the form of an interpretative case study. The use of this approach can be expected in support of logistic planning and decision making.

In the article a problem of modelling of standards of living is presented. The standards of living problem is described for real data set about 17 member states of European Monetary Union. It focuses on the quality of life and economic prosperity of the country. Models of Quality of life index, Prosperity index and Complete Standard of Living were proposed and analysed on the basis of cluster analysis algorithm TwoStep. Models were realised in SPSS Clementine.