Logistics and transport are becoming increasingly important in international trade relations. Logistic Performance Index (LPI) analyses the differences between countries, providing a general picture of customs procedures, logistics costs and the quality of the infrastructure necessary for overland and maritime transport. The aim of this article is to analyse the impact that each of the components that make up the LPI has on emerging countries' trade, employing a gravity model. Furthermore, the study also aims to detect possible advances in logistics in these countries, which are grouped into five regions (Africa, South America, Far East, Middle East and Eastern Europe) by comparing the first LPI data published in 2007 with the most recent data, released in 2012. The results obtained reveal that improvements in any of the components of the index cause the country to increase its volume of trade. Specifically, LPI components are becoming increasingly important for the countries in Africa, South America and Eastern Europe.

This article aims to analyse the importance of logistics performance in European Union (EU) exports over a sample period in order to detect possible advances on behalf of Member States. We will estimate several gravity equations using the Logistics Performance Index (LPI) and its components as characteristic proxy variables of trade facilitation. In order to avoid the possible heterogeneity caused by sample bias, we will employ the two-stage model proposed by Heckman. The estimations of the gravity models using the two-stage Heckman model for 26 EU countries lead to the conclusion that logistics were more important for exporting nations than importing nations in both

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Logistics and transport increasingly play a pivotal role in international trade relations. The Logistics Performance Index (LPI) measures the on-the-ground efficiency of trade supply chains or logistics performance. The aim of this paper is to propose a data envelopment analysis (DEA) approach to compute a synthetic index of overall logistics performance (DEA-LPI) and benchmark the logistics performance of the countries with LPI. Dealing with the six dimensions of LPI, the proposed approach uses DEA as a tool for multiple criteria decision making (MCDM). Furthermore, the paper also analyses the potential differences observed when using different variables, namely income and geographical area. Our findings suggest that the logistics performance depends largely on income and geographical area. High income countries are in the group of best performers, which is highly dominated by the EU.

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Many universities are currently doing important work not only on environmental issues, but also on social and economic matters, thereby covering the three dimensions of sustainability. This paper used data envelopment analysis to construct a synthetic indicator based on the variables that make up the UI GreenMetric. The aim was to quantify the contribution of universities to sustainability, rank all campuses accordingly, and evaluate specific aspects of their related institutional policies. First, cluster analysis was applied, yielding four homogeneous groups of universities. DEA was then applied to these clusters in order to construct the synthetic indicator. The proposed indicator, DEA-GreenMetric, revealed that the USA and the UK were the countries that were home to the greatest number of universities actively involved in all aspects of sustainability. In addition, this new index provides a complete ranking of universities, circumventing the issue of the duplicate scores assigned by UI GreenMetric. Finally, it can be seen that greater efforts are required for universities to improve their performance relating to environmental variables (energy, water use, and waste treatment) than to make improvements in infrastructure, transport, or education.

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