Background and Aim:
In 2024, the Guardian1 reported on the launch of the UK’s largest electric Bus fleet in Oxford, stating ‘The 159 new battery-powered buses will give Oxford more electric buses per capita than other cities including London, Glasgow and Leicester, under a pioneering arrangement in which the council will guarantee private operators faster journey times in return for investment.’ and
‘The move to make all Oxford buses zero-emission comes in contrast to the controversial decision to build the new East-West railway line between Oxford and Cambridge using diesel trains, rather than electrifying the track.’
The coursework requires each group to present a convincing argument using Business Analytics techniques (introduced throughout the BADM – 31768 module) to explore current decision making in the context of the shift of public transport fleets to a more sustainable mode.
You may explore local initiatives with respect to the bus network in Portsmouth or take a broader view on exploring national or international initiatives. However, be aware that available data may be restricted in certain cases.
Each group will have the opportunity to present their work to a panel for feedback, before submitting a group report with the aim to convince relevant stakeholders of the applicability of a proposed shift in transport mode or alternative decisions in the context, by presenting a rationale that is supported by insights drawn from the applications of business analytics.
The report must make use of data analytics tools that have been introduced in the module.
Objectives:
Develop an understanding of the context of the case study
The group is asked to familiarise themselves with the module content, the proposed data sources and the context of the coursework using the provided material as well as any relevant additional information you may find using resources that you consider to be reliable.
Identify critical factors in the context of transport fleet design and explore relevant data for investigation
Explore relevant literature or conventional wisdom that would support an argument for specific public transport modes. Identify relevant information that would be required to make an argument.
Explore relevant data
Review the Census (or other relevant data) information based on the information identified in previous objectives. See Section Data Access (next page) which identifies possible data access.
Present your findings to a panel of experts
You will present the proposed techniques in a 15min presentation to a panel to gather feedback for your final submission.
1 Source: https:// www.theguardian.com/world/2024/jan/14/oxford-becomes-uk-electric-bus- capital-159-vehicles-join-fleet
( BADM M31768 – Coursework Brief )
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Prepare and submit a report that outlines your rationale
Ensure that your presented insights are technically accurate, reproducible (e.g. outline any assumptions made, which data used, etc.) and justifiable (why this approach). It is your task to choose an appropriate format to convince potential stakeholders of the proposal in the context of public transport mode. You will also be required to include an evaluation of potential limitations to your approach.
Data Access
You are encouraged to engage with the UK Census data. You can find more information about the Census here.
While the latest Census took place in 2021, the data available is currently limited to some summarised information. Hence, it is recommended to review the data from 2011 which can be accessed via several sources, including Nomis or via UKdataservice.
Please be aware that you are not restricted to Census data and may wish to engage with other data sources.
Outputs:
Presentation
Each group has to present the work in a 15-min presentation on Monday, 26 April 2024. The presentation is not assessed but will provide you with an opportunity to get feedback on your proposed work.
Final report (max 1,000 words)
Each group has to submit one report presenting the proposed strategies that address the outlined objectives. Appendix 1 – the assignment of marks – has to be completed and attached to the final submission. The report has to be submitted in form of a digital copy to the relevant dropbox on Moodle by Friday, 1 May 2024. The final report is assessed and will form 50% of your module mark.