Consumer’s risk perception on the Belt and Road countries: evidence from the cross-border e-commerce

Abstract

Understanding consumer’s risk perception on the Belt and Road (B&R) countries is important for the development of cross-border e-commerce (CBEC) along these countries. However, most of the extant studies cannot properly analyze consumer’s risk perception due to the limited data collected by questionnaires. Therefore, this study proposes a text-mining-based framework to study consumer’s risk perception on the B&R countries based on massive textual online reviews collected from CBEC. In the proposed framework, the Latent Dirichlet Allocation model and sentiment analysis method are used to identify the main risk factors affecting consumer’s risk perception and calculate their sentiment score, the risk perception indicator is constructed to measure the magnitude of consumer’s risk perception. In the experiment, totally 66,661 reviews of the representative products from nine B&R countries are collected from Tmall Global. Six major risk factors are identified, and consumer’s risk perception on nine B&R countries is given.