Naslov
Forecasting Sales in Retail with XGBoost and Iterated Multi-step Ahead Method

Autori
Baržić, Mia ; Munitić, Naomi-Frida ; Bronić, Filip ; Jelić, Luka ; Lešić, Vinko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of International Conference on Smart Systems and Technologies (SST 2022) / - , 2022, 143-148

Skup
5th International Conference on Smart Systems and Technologies (SST 2022)

Mjesto i datum
Osijek, Hrvatska, 19.10.2022. - 21.10.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Time series forecast ; retail sales prediction ; XGBoost ; iterated multi-step ahead method

Sažetak
Due to shopping trends change, retailers are prompt to optimize their business processes in order to provide more personalized, faster and smarter user experience, grow revenue and reduce business costs. Retail operational decisions include product allocation, product replenishment points and vehicle routes for inventory renewal. In all of these areas, a distinctive contribution lies in accurate estimation of product demand. This paper focuses on forecasting sales in retail. The product sales is modeled by using XGBoost algorithm and iterated multi-step ahead method on the horizon of 7 days. Model inputs include real historical sales data, seasonality and working/non-working day indicators. Model is tested with a real dataset of five chosen products provided by an industry partner. Results are compared to the baseline linear model and show improvement of over 21%.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA