Online shoppers decide under two kinds of social information: electronic word-of-mouth (eWOM), which conveys other consumers' opinions, and observational learning (OL) information, which conveys their actions, such as sales and review counters. This paper examines how the two relate to customer decision-making and whether their influence depends on brand premium. Using 90 days of daily data (1 January–31 March 2018) on two smartphones sold through the same official flagship store on Taobao—the high-premium Apple iPhone X and the low-premium Huawei Honor V9—we decompose 6,239 screened reviews into seven content dimensions (authenticity, appearance, function and performance, young-user references, older-user references, logistics and customer service) and relate them to sales. Three findings emerge. First, review content differs systematically: iPhone X reviews are dominated by authenticity, performance and young-user references, Honor V9 reviews by older-user references, logistics and service. Second, opinion-based eWOM content is strongly associated with sales for both products, function-and-performance content most of all (r = 0.935 and 0.899), whereas the action-based OL cue of review volume tracks sales only loosely. Third, brand premium conditions which dimensions matter: in multivariate models only function and young-user content are positively associated with iPhone X sales, whereas function, logistics and service content are positively associated with Honor V9 sales. Premium-brand customers thus rely on a narrow set of product-centred cues, while for mass-market brands service-related eWOM carries additional decision-relevant information. Implications and limitations are discussed.

Xinna Zhao, Yanwen Zhu, Liming Zhai. The Effects of Electronic Word-of-Mouth and Online Observational Learning Information on Customer Decision-Making: Evidence from High- and Low-Premium Smartphones on Taobao. International Journal of Big Data Intelligent Technology (2026), Vol. 7, Issue 2: 128-139. https://doi.org/10.38007/IJBDIT.2026.070213.

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