A panel data approach for fashion sales forecasting
نویسندگان
چکیده
Sales forecasting is an important problem in fashion retail operations. In this paper, we propose a novel panel data based particle-filter (PDPF) model to conduct fashion sales forecasting. We evaluate the performance of proposed model in terms of sales quantity and color trend prediction by using real data from the fashion industry. The experimental results provide novel insights and practical guidance to operations managers on the use of panel data for fashion sales forecasting.
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