Towards a common measure of greenhouse gas related logistics activity using data envelopment analysis

Richard Holden, Bing Xu, Philip Greening, Maja Piecyk, Pratyush Dadhich

Research output: Contribution to journalArticle

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 transportactivity (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.
LanguageEnglish
Pages105-119
Number of pages15
JournalTransportation Research Part A: Policy and Practice
Volume91
Early online date6 Jul 2016
DOIs
StatePublished - Sep 2016

Fingerprint

Freight
Data envelopment analysis
Greenhouse gases
Logistics
Freight transport
Good practice
Benchmarking
Performance measurement
Emission reduction
Key performance indicators
Undesirable outputs
Monitoring

Keywords

  • Carbon measurement;
  • Logistics activity;
  • Benchmarking;
  • Data Envelopment Analysis

Cite this

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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 transportactivity (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.",
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Towards a common measure of greenhouse gas related logistics activity using data envelopment analysis. / Holden, Richard; Xu, Bing; Greening, Philip; Piecyk, Maja; Dadhich, Pratyush.

In: Transportation Research Part A: Policy and Practice, Vol. 91, 09.2016, p. 105-119.

Research output: Contribution to journalArticle

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