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Published on 21 February 2025
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Chang,Z. (2025). Research on Overseas Market Demand Forecasting Model for Light Industry Products Based on Data Mining. Journal of Fintech and Business Analysis,2(1),23-28.
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Research on Overseas Market Demand Forecasting Model for Light Industry Products Based on Data Mining

Zhou Chang *,1,
  • 1 Kunshan High School of Jiangsu Province, Kunshan, Jiangsu 215300, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/3049-5768/2025.21038

Abstract

Light industrial products have a significant share in international trade, and with the passage of time, the export volume of these products is also increasing year by year. From the revenue reports of Hikvision over the past 10 years, it can be seen that the sales of light industrial products, both domestically and internationally, are steadily increasing. Among the eight categories of light industrial products exported from China, five categories including tobacco and alcohol, textiles, cosmetics, gold and jewelry, and furniture show a positive growth in the number of exports. In the Vietnamese market, manufacturing and transportation are among the sectors that have the greatest impact on the growth of the Vietnamese economy. Surveys indicate that the volume of cargo transportation in Vietnam is increasing year by year, leading to a rising demand for transportation AGV robots. In the forecast model for cargo volume in the Vietnamese market, it is predicted that the volume of cargo transportation will gradually increase in the future, and therefore, the demand for pallet robots will also gradually increase with changes in cargo volume.

Keywords

light industrial products, overseas markets, demand forecasting, data analysis

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Cite this article

Chang,Z. (2025). Research on Overseas Market Demand Forecasting Model for Light Industry Products Based on Data Mining. Journal of Fintech and Business Analysis,2(1),23-28.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Journal:Journal of Fintech and Business Analysis

Volume number: Vol.2
ISSN:3049-5768(Print) / 3049-5776(Online)

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