2. Literature Review
In the literature, several researches have recently studied and described urban freight distribution. Most of the
studies propose general distribution models compliant with the City Logistics vision. These papers suggest
alternative network designs, investigating the advantages in terms of costs and greenhouse gases emissions. They
include the implementation of City Distribution Centers (McKinnon et al., 2012; Benjelloun and Crainic, 2008),
networks of satellite platforms close to the city center (Crainic et al., 2009; Perboli et al., 2011), modal shifts and
Intelligent Transportation Systems, ITS (Giannopoulos, 2009). All these papers are based on cooperative freight
transportation systems and carriers are seen as a service.
Other papers deal with the planning of City Logistics Service Providers’ (LSP) activities with two main purposes.
The first one is to support City Logistics service providers in performing a reliable and efficient service, while
reducing costs. This is the main task of vehicle routing problems. In particular, the reliability of the service is related
to the number of timely deliveries. Thus, several new models consider congestion and travel time variations in urban
areas, in order to avoid congested links and to respect delivery time windows. (Jiang & Mahmassani, 2013; Ehmke
et Al., 2012; and Crainic, 2010). The second purpose focuses on the environmental sustainability of urban freight
deliveries. LSPs play an important role to provide green services and products. Recently, new strategies and
collaborations focus on the reduction of the impact of urban goods distribution on the environment. In particular,
several studies investigate new solutions that allow to minimize the amount of CO2 emitted (Kara et al., 2007; Jabali
et al., 2012; Figliozzi, 2011; Rossi et al., 2013).
The above-mentioned literature highlights the common trends of considering LSPs as passive actors of the
system, i.e., they apply the distribution models proposed by other stakeholders (public authorities, owners of the
supply chain and manufacturers). On the contrary, LSPs are organizations, which adapt the delivery system rules to
their business model in order to maximize their profit. Such issue leads to the research question of this paper: how
the productivity of a LSP is linked to its operational delivery service. In fact, papers generally focus on the cost
reduction as almost unique way to increase CLPSs’ profit, disregarding the revenue component.
Moreover, very few papers discuss an efficiency analysis of LSPs. Examples of performance measurement look
at the benchmark of different companies analyzing their activity. Min and Joo (2006) develop a set of financial
benchmarks to identify best practices, implementing a Data Envelopment Analysis (DEA) for measuring the
operational efficiency of various profit or non-profit organizations. The operational efficiency is assessed through
input/output ratios. The input parameters selected by the authors are: account receivables, salaries and wages of
employees, operating expenses other than salaries and wages, and property and equipment. On the output side, they
measure the overall performance only considering the operating income. Thus, the authors take into account general
parameters, which are not strictly related to the daily activities. Wanke (2013) implements three-stage DEA models
and Stochastic Frontier Analysis (SFA) to investigate the efficiency of the largest trucking companies in Brazil. The
considered inputs are the number of branches, the employees, the fleet size, and the fuel consumption. The outputs
are total cargo transported (expressed by tons per year) and distance travelled (measured by the kilometers per year).
This paper also proposes an analysis of LSP performance on a year basis. Another example is provided by
Chandraprakaikul and Suebpongsakorn (2012), which benchmarks the performance of 55 logistics companies
applying DEA and Malmquist Productivity Index (MPI). The inputs include the net value of lands, the buildings and
the equipment, the shareholder fund, the operating cost, the cost of sales and/or cost of service, and the current
liabilities. Profits and revenues are considered as outputs. Anderson et al. (2005) investigate how new policy
measures affect operational activities of freight transport companies. The authors consider as important indicators of
operational activity the total number of rounds, the total time taken per round, the delivery time as % of the total
time taken, stationary time as % of the total time taken, the total distance travelled per round, the total vehicle
operating cost per round, and the total emissions of pollutants. According to the authors, these indicators describe
the operational, financial and environmental sustainability of vehicle rounds. Thus, they give an idea