Abstract
Abstract Pricing is a crucial decision for electronic fashion retailers. Motivated by various observed industrial practices in electronic retailing, we study in this paper the optimal Internet pricing schemes which employ price testing with Bayesian information updating following the Bernoulli process. This paper contributes to the literature and advancement of knowledge in a number of ways: (i) we propose an analytical model to study the Internet pricing problem with price-testing and Bayesian information updating for fashion retailers. (ii) We derive the closed-form expressions of the expected value of sampling information (EVSI) and the expected value of perfect information (EVPI) under the price testing scheme. (iii) We conduct the pre-posterior analysis and construct the optimal sampling plan with three different rules. (iv) We develop the optimal posterior pricing policies, with respect to the mean-risk and Value-at-Risk (VaR) objectives. Numerical analyses, which include the studies on EVPI and the efficient frontiers, are presented to generate more insights.
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