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Logistics plays an essential role in supply chain management to plan and coordinate the movement of products in a timely, safely and effectively way. The recent term Logistics 4.0 focusses on the specific applications of Industry 4.0 in the area of logistics and was created as an integral part of the Industry 4.0 concept. This study aims to contribute to the state-of-the-art about this topic by analysing and reviewing the scientific literature relating to Industry 4.0 applied to the logistics field. By means of a query on the Scopus database (www.scopus.com), 131 articles were retrieved and judged in line with the research topic. A bibliometric analysis identified the most relevant articles, authors, keywords, countries and journals on this subject. To the best of the authors' knowledge, this is the first systematic review of Logistics 4.0 using bibliometric analysis. Finally, the research gaps identified will provide a reference point that will encourage and guide interested researchers for future study. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

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This study investigates the issue of minimizing the environmental burden of a real closed-loop supply chain (CLSC), consisting of a pallet provider, a manufacturer and several retailers. A simulation model is developed under Microsoft Excel™ (Microsoft Corporation, Washington, US) to reproduce the flow of returnable transport items (RTIs) in the CLSC and to compute the corresponding environmental impact. Multi-objective optimization, including some relevant environmental key performance indicators (KPIs), is then carried out exploiting the commercial software ModeFRONTIER™ (ESTECO S.p.A., Trieste, Italy), to determine the settings that minimize emissions of the CLSC. In addition, economic and strategic metrics are taken into account in the optimization, to make the analysis more comprehensive. Three scenarios are considered (one "base" scenario and two scenarios examined in a sensitivity analysis) with different relative importance assigned to the metrics subject to optimization. Results show that the asset retrieving operations contribute to the environmental impact of the system to the greatest extent, mainly because of the quite relevant distance between Company A and its customers. Conversely, emissions due to the purchase of new assets contribute to the total environmental impact of the system to a very limited extent. Because the analysis is grounded on a real CLSC, the results are expected to provide practical indications to logistics and supply chain managers, to minimize the environmental performance of the system.

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