The DOI matches its Crossref record.
Comparative analysis of the carbon footprints of conventional and online retailing: A “last mile” perspective
Abstract
Purpose: The purpose of this paper is to focus on the carbon intensity of “last mile” deliveries (i.e. deliveries of goods from local depots to the home) and personal shopping trips. Design/methodology/approach: Several last mile scenarios are constructed for the purchase of small, non‐food items, such as books, CDs, clothing, cameras and household items. Official government data, operational data from a large logistics service provider, face‐to‐face and telephone interviews with company managers and realistic assumptions derived from the literature form the basis of the calculations. Allowance has been made for home delivery failures, “browsing” trips to the shops and the return of unwanted goods. Findings: Overall, the research suggests that, while neither home delivery nor conventional shopping has an absolute CO 2 advantage, on average, the home delivery operation is likely to generate less CO 2 than the typical shopping trip. Nevertheless, CO 2 emissions per item for intensive/infrequent shopping trips by bus could match online shopping/home delivery. Research limitations/implications: The number of items purchased per shopping trip, the choice of travel mode and the willingness to combine shopping with other activities and to group purchases into as few shopping trips or online transactions as possible are shown to be critical factors. Online retailers and home delivery companies could also apply measures (e.g. maximising drop densities and increasing the use of electric vehicles) to enhance the CO 2 efficiency of their logistical operations and gain a clearer environmental advantage. Practical implications: Both consumers and suppliers need to be made more aware of the environmental implications of their respective purchasing behaviour and distribution methods so that potential CO 2 savings can be made. Originality/value: The paper offers insights into the carbon footprints of conventional and online retailing from a “last mile” perspective.
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Citations
Cited by
Beitzen-Heineke, E. F., Balta-Ozkan, N., & Reefke, H. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.09.227 · Cited by 267
A review of the environmental implications of B2C e-commerce: A logistics perspective
Mangiaracina, R., Marchet, G., Perotti, S., & Tumino, A. (2015) · International Journal of Physical Distribution & Logistics Management · doi:10.1108/ijpdlm-06-2014-0133 · Cited by 257
A comparative analysis of carbon emissions from online retailing of fast moving consumer goods
van Loon, P., Deketele, L., Dewaele, J., McKinnon, A., & Rutherford, C. (2015) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2014.06.060 · Cited by 246
Self-citationKnown unknowns: Indirect energy effects of information and communication technology
Horner, N. C., Shehabi, A., & Azevedo, I. L. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/10/103001 · Cited by 177
Pohl, J., Hilty, L. M., & Finkbeiner, M. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.02.018 · Cited by 164
Metadata
- Authors
- Edwards, J. B., McKinnon, A. C., & Cullinane, S. L.
- Venue
- International Journal of Physical Distribution & Logistics Management
- Publisher
- Emerald
- Published
- 2010-02-02
- Volume
- 40
- Issue
- 1/2
- Pages
- 103-123
- ISSN
- 0960-0035 (ISSN-L)
- OpenAlex
- W1499964891
- Cited by
- 323
- References
- 0
- FWCI
- 22.49
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Comparative analysis of the carbon footprints of conventional and online retailing: A “last mile” perspective. https://app.cochat.ai/papers/10.1108/09600031011018055
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- Edwards, J. B., McKinnon, A. C., & Cullinane, S. L. (2010). Comparative analysis of the carbon footprints of conventional and online retailing: A “last mile” perspective. International Journal of Physical Distribution & Logistics Management. https://doi.org/10.1108/09600031011018055
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.