This model highlights some theoretical and practical implications associated with the design of a distribution
system of a LSP. In fact especially in recent years, the strong competition has led higher demand for efficiency in
particular in terms of customer service and cost reduction (Hoff et al., 2010). Efficient distributions systems are
becoming more and more important considering that transportation costs can account for up to 20% of the total cost
of a product. In this context, strategic fleet decisions involve considerable capital investment, and vehicles are
generally long-lived assets and there is an intrinsic uncertainty about demand they will serve over their lifetime, and
about the condition they will operate. These conditions make the risk associated with these decisions very high.
Thus, it is more and more important to design in a proper way the vehicle fleet in order to properly exploit these
kind of investments. From a theoretical point of view, this study represents a first attempt to develop a
comprehensive panel, that includes many operational aspects, to manage more efficiently the distribution system of
LSPs, measuring the main elements that affect its productivity. This is a crucial aspect that leads to another
important practical feature related to the structure of the urban environment and to its design. In urban areas,
logistics companies should develop proper strategies able to fit with the environment in terms of number of
customers, and kilometers. The benefits associated with the enhancement of the productivity are not only
economics, but environmental too. Nowadays, the level of pollution and more in general climate change, have
become significant drivers towards more efficient transportation. An improved level of productivity for a LSP, in
terms of number of stops for pick up and delivery activities reflects on a decreased number of vehicles for a LSP’s
fleet. In fact an optimized routing, together with a proper location of the warehouse and a better loading strategy,
can significantly increase the number of stops for a single van. Thus, a lower number of van properly loaded that
cover more efficiently a specific urban area leads to a lower level of CO2 emissions in the atmosphere. Therefore
the CL system that operates in the scheduling of logistics operations in urban areas and seeks for fast, accurate and
reliable pick- up and delivery tasks (Ehmke et al., 2012), appears to be an important element in achieving better
quality of life in urban areas in terms of air quality and traffic congestion. But unfortunately, city transportation
systems are characterized by a high level of complexity with often lack of knowledge and it is difficult to identify
precise elements that can enhance them. In fact there are many drivers that participate to the running process of
these systems and for this reason policy makers are not always able to implement efficient actions. Therefore, there
is a strong need for easy tools to support standards, procedures, solutions and good practices (Witkowski & KibaJaniak,
2012). In this context the proposed model has identified several areas of action wherein it is possible to
operate in order to improve the productivity of a LSP’s vehicle fleet with positive effects on the environment and in
terms of savings.