Towards a common measure of greenhouse gas related logistics activity using data envelopment analysis. (September 2016) - Holden, R.; Xu, B.; Greening, P.; Piecyk, M.; Dadhich, P.
Highlights: We use DEA to benchmark road freight companies with different operational traits. The DEA model is aimed at minimising GHG emissions. This model is potentially useful as a tool for companies and for aggregate reporting. Improving fleet operations is more than optimising individual vehicles. Abstract: Monitoring company emissions from freight transport is essential if future greenhouse gas (GHG) reductions are to be realised. Modern economies are characterised increasingly by lower density freight movements. However, weight-based measures of freight transport activity (tonne-kilometre, tonnes lifted) are not good at describing volume-limited freight. After introducing the need for performance measurement, the problem of benchmarking is outlined in more detail. A context-dependent undesirable output data envelopment analysis (DEA) model, designed to be sensitive to business context, is then tested on a simulated set of fleet profiles. DEA can produce more consistent measures of good-practice, compared to ratio-based key performance indicators (KPI), providing emission reduction targets for companies and an aggregate reporting tool.