Data envelopment analysis models to support the selection of vehicle routing software for city logistics operations

In city logistics operations, vehicle routing is critical for successful freight delivery execution. Optimal routing, however, may not be performed when manual routing methods are implemented, due to their inability to cope with a number of delivery constraints such as hard delivery time windows. The use of an automated vehicle routing software by freight carriers, is usually the preferred option, as it may increase customer service and reduce operational costs. The evaluation and selection of automated routing software has become increasingly difficult for decision makers due to a large number of software products available and the great variety of features and capabilities they offer. This paper first develops a data model to capture all the significant attributes that characterize a routing software. The attributes are measured with ordinal data as they mainly express qualitative issues. Then, it presents a data envelopment analysis (DEA) model that aids the selection procedure by estimating the index Total Performance/Price that expresses the commonly used “value for money” criterion. This index is able to identify those routing software that are considered as best buys. Moreover, this paper proposes a DEA model to distinguish the best alternative from the “best buys” cases. A case study illustrates the proposed methodology.