Abstract: The concept of City Logistics (CL) has emerged to improve the impacts of last mile freight distribution in urban areas. In this paper, a System Dynamics (SD) model exploring the dynamics of the diffusion of a ICT platform for CL management across different populations is proposed. For the development of the model two sources have been used. On the one hand, the major diffusion variables and feedback loops are derived from a literature review of existing diffusion models. On the other hand, the parameters are represented by the value propositions delivered by the platform as a response to some of the users’ needs. To extract the most important value propositions the Business Model Canvas approach has been used. Such approach in fact focuses on understanding how a company can create value for her target customers. These variables and parameters are thus translated into a SD diffusion model with three different populations namely municipalities, logistics service providers, and own account carriers. Results show that, the three populations under analysis fully adopt the platform within the simulation time frame, highlighting a strong demand by different stakeholders for CL projects aiming at carrying out more efficient urban logistics operations.
Abstract: The area of Project Risk Management (PRM) has
been extensively researched, and the utilization of various tools and
techniques for managing risk in several industries has been
sufficiently reported. Formal and systematic PRM practices have
been made available for the construction industry. Based on such
body of knowledge, this paper tries to find out the global picture of
PRM practices and approaches with the help of a survey to look into
the usage of PRM techniques and diffusion of software tools, their
level of maturity, and their usefulness in the construction sector.
Results show that, despite existing techniques and tools, their usage is
limited: software tools are used only by a minority of respondents
and their cost is one of the largest hurdles in adoption. Finally, the
paper provides some important guidelines for future research
regarding quantitative risk analysis techniques and suggestions for
PRM software tools development and improvement.