Low emission logistics have become an expected and desired goal in all fields of transportation, particularly in the European Union. Heavy-duty trucks (HDTs) are significant producers of emissions and pollution in inland transports. Their role is significant, as in multimodal transport chains truck transportation is, in most cases, the only viable solution to connect hinterlands with ports. Diesel engines are the main power source of trucks and their emission efficiency is the key challenge in environmentally sound freight transportation. This review paper addresses the academic literature focusing on truck emissions. The paper relies on the preliminary hypothesis that simple single solutions are nonexistent and that there will be a collection of suggestions and solutions for improving the emission efficiency in trucks. The paper focuses on the technical properties, emission types, and fuel solutions used in freight logistics. Truck manufacturing, maintenance, and other indirect emissions like construction of road infrastructure have been excluded from this review.
Big Data may introduce new opportunities, and for this reason it has become a mantra among most industries. This paper focuses on examining how to develop cost and sustainable reporting by utilizing Big Data that covers economic values, production volumes, and emission information. We assume strongly that this use supports cleaner production, while at the same time offers more information for revenue and profitability development. We argue that Big Data brings company-wide business benefits if data queries and interfaces are built to be interactive, intuitive, and user-friendly. The amount of information related to operations, costs, emissions, and the supply chain would increase enormously if Big Data was used in various manufacturing industries. It is essential to expose the relevant correlations between different attributes and data fields. Proper algorithm design and programming are key to making the most of Big Data. This paper introduces ideas on how to refine raw data into valuable information, which can serve many types of end users, decision makers, and even external auditors. Concrete examples are given through an industrial paper mill case, which covers environmental aspects, cost-efficiency management, and process design.
This paper analyses cost aggregation in a supply chain. It provides a literature overview on the key concepts of cost aggregation, multimodal transport, logistic chain and maritime transport. The focuses on the value adding process with logistics data and assesses the costs accumulation during the transport process. The paper also reveals multimodal impacts on the logistics costs. The research data is obtained from the costing system of a large export company. The company exports round 90% of its production and mostly to the European markets. The research data contains a sample of 929 invoiced orders to the largest market of the mill. The research results indicate empirical evidence of the cost-function properties. This type of an approach is rare in logistics literature as these detailed data sets are highly difficult to obtain. The article concludes by addressing future research task and directions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.