Bayesian Network Evidence on Price, Electronic Word of Mouth, and Seasonality in Amazon Product Sales Performance
Year: 2026
Type: article
Abstract: This study examines the associations of price, eWOM, and seasonal review activity with product sales performance in cross-border e-commerce. The analysis uses 3,886 products from Amazon's All Beauty category and treats sales rank as a proxy for relative sales performance. A compact Bayesian network links price level, eWOM strength, peak review season, and sales performance. Conditional probabilities are estimated with Laplace smoothing, while chi-square tests and Cramer's V assess the stability and strength of the observed associations. Products with high eWOM strength have a 48.9% posterior probability of high sales performance, compared with 19.4% for the medium group and 14.3% for the low group. Price differences are small, and seasonal differences are also limited. The strongest multi-factor combination consists of medium price, high eWOM strength, and a spring review peak, with a posterior probability of 58.7%. The results indicate that credible review activity is more closely associated with strong sales performance than price level or seasonality. The findings support a management approach that gives priority to genuine review quality, uses controlled price tests, and treats seasonal timing as supporting evidence rather than a primary decision rule.
Author: Runzi Wang
Institution: Nanyang Technological University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7225146795