In this paper, we present a review of city logistics modeling efforts reported in the literature for urban freight analysis. The review framework takes into account the diversity and complexity found in the present-day city logistics practice. Next, it covers the different aspects in the modeling selection process that includes (1) the stakeholders’ involvement (2) the objective of modeling (3) the defining criteria i.e. the descriptor for modeling purpose and (4) the viewpoint for achieving objective i.e. the perceptive. This review argues that these factors are evidently demonstrating forces behind urban freight transportation and thus are more determinative for carrying out urban freight modeling. The review analyzes the trends of city logistics modeling research in terms of its relevance to city logistics problems and attempts to identify gaps in modeling urban freight domain

This research shows how to use historical delivery data to predict future delivery results by applying address intelligence. The application of multiple linear regression techniques supports the development of address intelligence identifying and predicting the improvement potential (rework) for other zip code areas. The research has been successfully applied for a logistics parcel service company. In our case the application of address intelligence has shown that pre-delivery contact with the customer about the delivery time window seems to be the most promising concept to guarantee efficient delivery