Prevention of Food Waste in the Food Retail Industry using Data Mining and Data Analysis Techniques

Ethell, Matthew (2014) Prevention of Food Waste in the Food Retail Industry using Data Mining and Data Analysis Techniques. Diploma thesis, Dublin, National College of Ireland.

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Exploratory analysis was conducted on the Ta Feng retail datasets which cover a four month period from November 2000 to February 2001. The aim of the study was to explore factors such as the proximity of the customer to the retail outlet and the age group of the customers to determine their effect on consumer spending. With this information it is hoped to develop more efficient stock purchasing in the future. Several software applications were used in the study such as R, Excel, Python and WEKA in order to explore the aforementioned factors.

It was found that proximity to the retail outlet may affect consumer spending and so it would be important to know the number of customers who reside close to the retail outlet. Certain age groups were found to have higher spending patterns than others, so it would be wise to tailor stock purchases to the needs of these age groups. This is a preliminary study that lays the foundation for future stock purchasing analysis that will lead to efficient stock purchasing. Through improved stock purchasing information it is hoped to reduce waste, which is a huge financial loss to the supermarket industry.

Item Type: Thesis (Diploma)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Higher Diploma in Science in Data Analytics
Date Deposited: 15 Dec 2014 15:39
Last Modified: 15 Dec 2014 15:39

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