Title: A method of forecasting cross-border e-commerce stocking for SMEs based on demand characteristics and sequence trends under sustainable development strategy

Authors: Hua Yang; Lihui Yu

Addresses: School of Finance and Business, Zhongshan Torch Polytechnic, Zhongshan, 528436, China ' School of Finance and Business, Zhongshan Torch Polytechnic, Zhongshan, 528436, China

Abstract: With the continuous acceleration of economic globalisation, cross-border e-commerce enterprises have started to apply big data technology to find business information, among which the accurate forecast of stock availability has become an important influencing factor on consumers' online shopping experience. In order to improve the accuracy of cross-border e-commerce stocking prediction, this study first analyses the demand feature-based selection and prediction method, followed by the analysis of the serial trend-based stocking prediction method, and then proposes a stocking prediction method based on demand features fused with serial trend, and finally analyses the results of cross-border e-commerce stocking prediction for SMEs by the proposed method. The results show that the contribution rate of class A goods is the highest, which can be considered to build a stocking warehouse overseas for stocking, while stocking at the origin, and using multiple batches of small lot stocking to reduce inventory costs ensuring capital security.

Keywords: sustainable development; big data; demand characteristics; sequence trends; cross-border e-commerce; stocking forecast.

DOI: 10.1504/IJCSYSE.2023.132908

International Journal of Computational Systems Engineering, 2023 Vol.7 No.2/3/4, pp.57 - 66

Received: 16 Aug 2022
Accepted: 21 Oct 2022
Published online: 16 Aug 2023 *

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