- Title
- Cluster analysis for group selection in launch sales predictions
- Creator
- Watchurst, Lee
- Subject
- Gqeberha (South Africa)
- Subject
- Eastern Cape (South Africa)
- Subject
- Cluster analysis
- Date Issued
- 2021-04
- Date
- 2021-04
- Type
- Master's theses
- Type
- text
- Identifier
- http://hdl.handle.net/10948/52003
- Identifier
- vital:43447
- Description
- One way for businesses to stay ahead in a competitive market is through the launch of new products and planning for these launches optimally. This includes ordering the correct quantity of stock in advance as well as maintaining these stock levels while the item launches. However, holding too much stock in warehouses can affect the business costs adversely. This research proposes the use of cluster analysis techniques to determine the up-front purchase quantity by identifying similar items and using their initial quantities sold. Products will be grouped based on their numerical and categorical attributes. Once the data is clustered, the Bass model will be used to obtain a sales profile for the new item. The Bass model is a popular choice for product life cycle planning due to the emphasis placed on the timing of adoption. The study will make use of data from a retail and wholesale company that sells, in part, single use items. With the planning for new launches being a key problem point in many companies, this research aims to optimise the planning process and ensure product launch success across stores.
- Description
- Thesis (MSc) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 2021
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (vii, 81 pages)
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Science
- Language
- English
- Rights
- Nelson Mandela University
- Rights
- All Rights Reserved
- Rights
- Open Access
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