Price and its forecasting of Chinese cross-border E-commerce

Abstract

Purpose Cross-border e-commerce in China has been booming in recent years. This paper aims to study pricing in Chinese cross-border e-commerce companies and focuses on the baby food market, which is simply examined as a case study to highlight broader implications. In this intensely competitive sector, the biggest challenge faced by such companies is ensuring that they are in a position to be able set prices in the short-term to maximize their competitive advantage and profitability. The study of pricing will help management to make correct operational decisions. Design/methodology/approach This study utilizes transaction data, which were obtained from the Taobao e-commerce platform. Taobao is the largest e-commerce retail platform in the world. We analyzed factors, including business models, homogeneity, reputation ratings and sales volumes, which may affect pricing. Findings This study found that consumers in the baby food sector of Chinese cross-border e-commerce are not price-sensitive. Consumers are reputation-rating-sensitive. The reputation ratings of sellers affect the price dispersion in e-commerce markets. The Core Price Dispersion Rate Model not only considers the prices but also takes sales volumes into account in the calculations. Finally, based on Gaussian processes, a model was developed for price forecasting in the area of cross-border e-commerce. The experimental results show that the proposed method is highly valuable for price forecasting. Originality/value This study provides a novel understanding of the baby food sector in the Chinese cross-border e-commerce market by examining the business model, price dispersion, reputation rating and correlation between the reputation of sellers, prices and sales volume. Furthermore, a model for price forecasting is proposed.