| Journal: | Computación y sistemas |
| Database: | |
| System number: | 000560804 |
| ISSN: | 1405-5546 |
| Authors: | Taquía Gutiérrez, José Antonio1 |
| Institutions: | 1Universidad de Lima, Instituto de Investigación Científica, Lima, Lima. Perú |
| Year: | 2023 |
| Season: | Abr-Jun |
| Volumen: | 27 |
| Number: | 2 |
| Pages: | 545-552 |
| Country: | México |
| Language: | Inglés |
| English abstract | Bayesian approach was applied to the management of the supply chain in a dynamic food product portfolio for a company in the retail sector. We propose a quasi-experimental method considering pre and posttest and a control group. The sample size of 93 products, out of a population of 120 products from two categories: classic sauces and gourmet sauces. R and Python programming languages were used and libraries for random sampling of the a priori distribution of the products to obtain posterior values área presented on the research. Forecast accuracy increased with the Bayesian approach by 10%. Likewise, it was possible to reduce the coverage inventory from 2 to 1.2 months and the discrepancy between the values of the Bayesian estimate with the traditional method was possible to reach a 5% error in the variation. |
| Keyword: | Supply chain, Bayesian approach, Retail products, Critical fractile, Balanced operations |
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