Implications of express delivery business modelling in the last mile industry

WORTH, Tracey Elisabeth (2021). Implications of express delivery business modelling in the last mile industry. Doctoral, Sheffield Hallam University.

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Link to published version:: https://doi.org/10.7190/shu-thesis-00438

Abstract

The more successfully the Last Mile Logistics (LML) industry delivers its service, the greater the chance of delivering the Customer Promise for retailers. The motivation for this research was, to better understand the expectations and demands of online customers and the effect thereof on the LML provision. Previous research has sought to apply an understanding of business and operational models to the home delivery service, including vehicle route optimisation and delivery innovation (Perboli, et al., 2018). The LML industry is complicated, somewhat illstructured, relying on multiple and cross-functional approaches that must often be changed with immediate effect, subsequently destabilising the delivery provision. This research addresses the “Implications of express delivery business modelling in the last mile industry” arising from an initial study. This research critically examines key business models as well as the overall governance of the UK LML industry. It then goes onto develop an LML business model. This research addresses the complexity of the end customers’ experiences, recognising the impact of technology, that supports the online customer and its effects on the LML industry. The research identifies a solution for a more efficient LML Express industry business model based on Parmentier and Gandia’s (2017) multi-sided platform model. In 2015, an industry roundtable discussion focus group raised issues affecting the LML industry. A five-year longitudinal last mile delivery survey followed, with an in-depth company study of one leading UK LML and one-to-one interviews with eight leading LML professionals. The results establish significant themes regarding delivery for the customer, and LML delivery service industry. Throughout the research, the reliability of current LML business models and practices were identified. Analysis showed a lack of confidence implementing rigid business models in multi-channel and directional flow of demand, in a fluid marketplace. The research conclusion highlights need to engage with a multi-sided platform business model, incorporating technology, within the customer demand chain. This research provides a solution in the form of a business model platform, that might be used by an LML across the whole or part of the business.

Item Type: Thesis (Doctoral)
Contributors:
Thesis advisor - Gorst, Jonathan [0000-0002-3606-8766]
Thesis advisor - Shahidan, Malihe [0000-0003-0467-6318]
Additional Information: Director of studies: Dr. Jonathan Gorst / Thesis supervisor: Dr. Malihe Shahidan.
Research Institute, Centre or Group - Does NOT include content added after October 2018: Sheffield Hallam Doctoral Theses
Identification Number: https://doi.org/10.7190/shu-thesis-00438
Depositing User: Colin Knott
Date Deposited: 09 May 2022 15:26
Last Modified: 11 Oct 2023 15:17
URI: https://shura.shu.ac.uk/id/eprint/30212

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