Uppsats
What Drives the Thirst? : A Multiple Regression Analysis of Beer Sales in Sweden
Kandidat-uppsats
KTH/Sannolikhetsteori, matematisk fysik och statistik
Publicerad: 2026
Språk: Engelska
Sammanfattning
This thesis examines which product characteristics are related to beer sales in Sweden. The study is based on yearly article-level sales data from Systembolaget and focuses on how price, packaging, alcohol content, beer style, and country of origin are associated with beer sales measured in litres. This is relevant because the Swedish alcohol market is strongly regulated. As a result, product characteristics become especially important for how products compete and how consumers choose between them. The analysis is based on secondary data from 2025. After cleaning the data and removing products that were not directly comparable, the final sample consisted of 6127 beer products. Ordinary Least Squares regression was used to study the relationship between sales and the selected product characteristics. Since the first model did not meet the regression assumptions sufficiently well, the analysis was refined through grouping of categorical variables, diagnostic checks, variable transformations, and subset modeling. The final model uses log-transformed sales and divides the beers into two groups: lower-priced and higher-priced beers, based on price per liter. In both groups, price, volume, and alcohol content show the clearest relationship with sales. Beers with higher prices are associated with lower sales, while beers with larger volume and higher alcohol content are associated with higher sales. Bottles are also associated with lower sales than cans in both groups. Country of origin and beer style also appear to matter, but their effects differ more between the two segments. These differences are clearest in the high-price segment, where more country-of-origin and beer-style categories show significant effects.
Information
- Författare
- Gärtner, Elliot, Hermansson, Gustav
- Lärosäte / institution
- KTH/Sannolikhetsteori, matematisk fysik och statistik
- Publiceringsdatum
- 2026
- Uppsatstyp
- Kandidat-uppsats
- Språk
- Engelska
Utforska vidare
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