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Network configuration and optimisation for Omni-Channel retailing supply chain (REF: SF18/BAM/LI)

  • Full or part time
    Dr G Li
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Omni-channel retailing, in which bricks and mortar joins with other channels such as TV, mobile, tablet, catalogue, and social media as a single means of transaction (Bamfield, 2013), is believed to be the ‘next big trend’ and the future of retailing. The overwhelming development of this trend is greatly influencing the retail industry both in the UK and overseas, with UK companies like Tesco, John Lewis, and other large retailers making manifest their ambitions to become leaders in this retailing revolution by developing their own omni-channels.A significant number of retailers, however, including John Lewis and Tesco, are finding that achieving the omni-channel is easier said than done, and the entire retail industry is facing many obstacles to omni-channel development. Therefore, although many retailers continue to pursue the dream of such development, most of these are facing the problem that consumer expectations continue to outpace retailer ability to deliver a consistent cross-channel experience. The goal of ‘buy anywhere, get anywhere, and return anywhere’ greatly challenges retailers’ supply chains (Baird and Kilcourse, 2014). The traditional supply chain design for brick-and-mortar store or e-commerce cannot satisfy the current Omnichannel retailing demand.

This project will investigate the network configuration and optimisation of Omni-channel retailing supply chain. In particular the following objectives will be achieved:

(1) To understand the network configurations for different products. Different products may have different requirements on the supply chain network configurations. This project will identify the different configurations from different dimensions and explicate the requirements for different configurations.
(2) To develop network design models to optimise the supply network under different configurations. Structural properties of the network will be explored. The research methods used in this project will be mainly quantitative methods, in particular, empirical research or mathematical modelling will be extensively used.

The successful applicant will demonstrate an understanding of at least of the key operations and supply chain management regimes, i.e. supply network design, supply chain integration, supply chain relationship management, distribution, fulfilment, the interface between marketing and operations and a willingness to investigate across those areas in the digital age. A strong quantitative background or computer skills will be desirable.

Eligibility and How to Apply:
Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. SF18/…) will not be considered.

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality and is a member of the Euraxess network, which delivers information and support to professional researchers.

Funding Notes

Please note this is a self funded project and does not include fees.

References

(1) G. Li and S. F. W. T. Lim. Last-mile supply network configuration in omnichannel retailing: Hypotheses and Simulation Framework. Proceedings of 21st Annual CIM Symposium – Globalisaton 2.0. 28th-29th, September, 2017.
(2) W. Yan, Y. Xiong, J. Chu, G. Li, Z. Xiong, Clicks versus Bricks: the role of durability in marketing channel strategy of durable goods manufacturers, European Journal of Operational Research. 2017, Forthcoming.
(3) G. Li and Y. Zhou. Strategically decentralize when encroaching on a dominant supplier. International Journal of Production Research. 2016, In Press.
(4) Y. Xiong, P. Zhao, Z. Xiong and G. Li. The impact of product upgrading on the decision of entrance to a secondary market. European Journal of Operational Research, 2016. In Press.
(5) G. Cao, Y. Duan, G. Li. Linking business analytics to decision making effectiveness: a path model analysis. IEEE Transactions and Engineering. 2015, 62(3): 384-395.
(6) Y. Xiong, G. Li et al. Dynamic pricing models for used products in remanufacutring with lost-sales and uncertain quality. International Journal of Production Economics. 2014, 147: 678-688.
(7) Y. Xiong and G. Li. The value of dynamic pricing for cores in remanufacturing with backorders. Journal of the Operational Research Society. 2013, 64:1314-1326.
(8) Y. Zhou, Y. Xiong, G. Li, Z. Xiong and M. Beck. The bright side of manufacturing-remanufacturing conflict in a decentralised closed-loop supply chain, International Journal of Production Research. 2013, 51(9): 2639-2651.
(9) Y. Xiong, Y. Zhou and G. Li. Don’t forget your supplier when remanufacturing, European Journal of Operational Research. 2013, 230 (1): 15-25.

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