| Feb. 13, 2024, 4:20 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 68030, "fields": {"project": 16290, "organisation": 2, "amount": 285246, "start_date": "2015-12-14", "end_date": "2018-12-14", "raw_data": 189807}}]
|
|
| Jan. 30, 2024, 4:26 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 60850, "fields": {"project": 16290, "organisation": 2, "amount": 285246, "start_date": "2015-12-14", "end_date": "2018-12-14", "raw_data": 171485}}]
|
|
| Jan. 2, 2024, 4:16 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 53710, "fields": {"project": 16290, "organisation": 2, "amount": 285246, "start_date": "2015-12-14", "end_date": "2018-12-14", "raw_data": 144387}}]
|
|
| Dec. 5, 2023, 4:25 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 46453, "fields": {"project": 16290, "organisation": 2, "amount": 285246, "start_date": "2015-12-14", "end_date": "2018-12-14", "raw_data": 126569}}]
|
|
| Nov. 27, 2023, 2:16 p.m. |
Added
35
|
{"external_links": []}
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
43
|
[{"model": "core.projectfund", "pk": 39196, "fields": {"project": 16290, "organisation": 2, "amount": 285246, "start_date": "2015-12-14", "end_date": "2018-12-14", "raw_data": 83355}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 118993, "fields": {"project": 16290, "organisation": 20530, "role": "PP_ORG"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 118992, "fields": {"project": 16290, "organisation": 20531, "role": "PP_ORG"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 118991, "fields": {"project": 16290, "organisation": 20532, "role": "COLLAB_ORG"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
41
|
[{"model": "core.projectorganisation", "pk": 118990, "fields": {"project": 16290, "organisation": 13151, "role": "LEAD_ORG"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 74875, "fields": {"project": 16290, "person": 22292, "role": "RESEARCH_PER"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 74874, "fields": {"project": 16290, "person": 22293, "role": "COI_PER"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 74873, "fields": {"project": 16290, "person": 15743, "role": "COI_PER"}}]
|
|
| Nov. 21, 2023, 4:44 p.m. |
Created
40
|
[{"model": "core.projectperson", "pk": 74872, "fields": {"project": 16290, "person": 16914, "role": "PI_PER"}}]
|
|
| Nov. 20, 2023, 2:06 p.m. |
Updated
35
|
{"title": ["", "Dynamic Pricing in the Ferry Industry"], "description": ["", "\nChoosing the "best" ticket prices is one of the key challenges in the ferry industry, especially for ferry operators providing a service to both individuals and freight. When setting the ticket price, the operators need to (1) forecast the demand for ferry services by various types of passengers and their vehicles; (2) decide how much space should be allocated to different vehicle types; and (3) estimate how easily vehicles can be packed into the available deck space. \n\nForecasting demand, finding the most profitable allocation of space to different customers, and pricing of tickets fall under the umbrella term of Revenue Management (RM), which was originally developed for airlines, but is applicable across a wide-range of industries. What is new in this first part of the project is the inclusion of packing. By incorporating optimal packing of vehicles on the ferry into RM, we will find pricing and allocation solutions that increase the efficiency of ferry services and ensure the pricing properly reflects the cost of packing a vehicle into the limited deck space.\n\nTraditionally, RM has focused on maximising the revenue on each individual journey, but there is a need to look at the bigger picture and consider the effects of prices on the long-term profitability of the operator. Ferries are used by tourists who travel relatively infrequently and by regular customers, e.g. freight, commuters and regular coach services. By optimizing revenue in the longer term, e.g. over one year, as well as considering individual sailings, we will be able to take account of the total contribution of regular customers. For example, a freight company that operates year round or commuters who use the ferry regularly should not be priced out of the market during the peak summer season, but should be offered a price that reflects their long-term value to the company. Surprisingly little work has been carried out in this area, which is relevant to nearly all transport providers and is vital to avoid over-pricing tickets for regular customers at peak times. \n\nThrough working with P&O Ferries and Red Funnel, who operate ferries between mainland Britain and the Continent, and the Isle of Wight, respectively, we will use real data to inform the models. These real data are collected from various internal or external systems/sources (e.g. ticket booking systems, company's websites, frontline operating systems, marketing campaign records, market competitiveness reports, etc.). This project will first look at how to link these data together so that they could be used in building and testing our proposed quantitative models. The result of this project will therefore become a good example of utilising the potential of "Big Data". \n\nAfter collecting and preparing the data, our models will be developed to estimate the ticket prices which maximise revenue for the ferry operator. Improving revenues will be achieved in two ways: (1) increasing the number of vehicles that can be packed onto the ferry thanks to more effective packing algorithms; (2) optimizing prices based on forecast demand for different sailings. Improving the mix of vehicles on the ferry and the way they are packed will increase the efficiency of ferry services, having a positive environmental impact. \n\nThe work has wide-ranging implications in a number of industry sectors, particularly in optimal pricing for freight, where packing needs to be taken into account when setting delivery charges. Developing methods for optimizing revenue in the long-term could improve the pricing in any industries in which there is a mix of regular and occasional traffic.\n\n"], "extra_text": ["", "\n\nPotential Impact:\nThe proposed project will bring beneficial impact to a wide range of stakeholders. We consider it essential that the research work feeds into and back from real-world applications and our collaborators will of course have the opportunity to bring ideas into the research, and frame the problems we are trying to tackle, as well as hearing our results first hand. Our partners, P&O Ferries and Red Funnel, will thus gain insight into how to employ new models to understand their customers so as improve their Revenue Management (RM) strategies. Members of RMAPI, the society for RM professionals within the UK, will also have opportunities to gain from the work and provide feedback on its direction through seminars and networking.\n\nThe generic tools that we develop as part of this project will be freely available for download from the project website, alongside YouTube videos explaining the key ideas of the methods and relevant articles written by the research team. Smaller-scale organisations will therefore have access to new technology and resources, without undergoing the risk associated with research and development. \n\nThe University of Southampton's close link with RMAPI is vital for the transformation of academic results into real-world applications, with obvious benefits for UK industry. Dr Currie is a regular presenter at the RMAPI conferences and this will help with dissemination of results.\n\nTeaming up three researchers from different specialities to apply mathematical models within a Revenue Management project will obviously benefit the field of Operational Research, but due to the strong industry relevance of the research, we would expect a wider academic community in computer science and social science to gain from the deepening of expertise in this area. Through attending conferences, holding workshops and seminars, and liaising with industrial partners, the project team will develop and strengthen their research and leadership skills. In particular, they will be more capable to lead or participate in high-impact industry-oriented projects in the future. Having more effective interfaces between Higher Education Institutes and Business is one of the key elements in helping the UK to become an innovative economy.\n\nIncreasing the efficiency of ferry transportation will reduce fuel bills and hence reduce costs and greenhouse emissions. Increasing the revenue available to ferry operators will make the industry more sustainable within the UK. Being an island nation, reliant on shipping for most importing and exporting, as well as foreign travel, a sustainable shipping operation is vital for a healthy economy.\n\nThe project will enable value to be extracted from the ever-growing quantities of online and offline data. In recent years, there has been increasing investment in data acquisition, and how to utilize "Big Data" is a topical question for both government and business. This research will become a classic example of how to create knowledge efficiently and effectively from data to face emerging challenges. It may not be possible to measure this impact directly but both the academic community and society will draw inspiration from this project. \n\nA further impact of this project is on people. We will develop and present a workshop to school children, demonstrating the importance of mathematics outside of the classroom. In addition, by providing training and experience for the PDRA working on the project, and by sharing our experiences with students on the MSc programmes in Operational Research and Management Sciences at the University of Southampton, we will be increasing expertise in the UK in this vital area of OR.\n\nIn summary, the project results will be useful for a wide range of audiences to achieve policy goals, social goals or, most likely, to achieve commercial goals.\n\n\n"], "status": ["", "Closed"]}
|
|
| Nov. 20, 2023, 2:06 p.m. |
Added
35
|
{"external_links": [63494]}
|
|
| Nov. 20, 2023, 2:06 p.m. |
Created
35
|
[{"model": "core.project", "pk": 16290, "fields": {"owner": null, "is_locked": false, "coped_id": "0b99b8f9-52d4-4ef9-878e-cc2893266bc9", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 83338, "created": "2023-11-20T14:01:48.202Z", "modified": "2023-11-20T14:01:48.202Z", "external_links": []}}]
|
|