Abstract: One of the remarkable differences between online retail and traditional physical storefront operation is that there are a lot of consumer returns caused by non-quality reasons. The proper analytical expression of returns in the e-commerce environment is a key issue of inventory and pricing optimization and the effective product information disclosure strategy. The online shopping behavior could be divided into two-stage decision processes of the purchase decision and the return decision. The decisions are mainly based on the estimated valuation observed by consumers through browsing introduction pages and the perception differences revealed after obtaining the product. Based on the mechanism of returns, the uniform distribution of perceived value in Hotelling model and existing research is hypothesized, and the characteristics of the purchase probability and the return probability in both daily sales period and promotion period are analyzed. Expected profit models are established, and analytical solutions of the optimal order quantity are derived. Computational methods for the optimal solutions of the price in daily sales period, the price discount in promotion period, and the maximum expected profits are also demonstrated. Taking the cost parameters in existing joint pricing and inventory optimization study for reference, a set of numerical examples is made, in which perceived value and perception differences are verified to obey the more general distribution with different correlation coefficients. The change rule of the maximum profit with the information distribution beautification degree, and the influence of the correlation on the effectiveness of the beautification strategy are studied. The research shows that:customer returns in the promotion period are affected by two reverse effects, which are the increase of return rate due to the impulse buying and the decrease of return rate caused by the loss of returns due to opportunity costs, and the probability of impulsive buying increases with higher prices; the purchase and return rate model in e-commerce environment built from the perspective of perceived value and perception difference is in accordance with the existing empirical study that the return rate increase with the price, and it can also explain the reason for the high return rate after steep price reduction; when the selling price, the purchase price and the residual value meet certain conditions, the merchants adopt the appropriate information disclosure beautification strategy can improve the profit to some extent; the degree of information beautification increases with the price and the residual value, and the extent to information beautification in promotion period is higher than that in the daily sales period; the profit of the product with moderate linear correlation between perceived value and perceived difference is lower than that of the product with low or high linear correlation; Information beautification strategy is more effective on products with higher linear correlation. The return model from the perspective of perceived value and perception difference is built, which is more consistent with the actual situation and the results of empirical studies. Based on that return model, the research of the pricing and ordering optimization and the beautification strategy of information disclosure can provide better decision support for online retailers.

Key words: online retail, reverse logistics, inventory optimization, pricing decision, valuation uncertainty