<p>Pricing a global product differently across multiple regions is a common but controversial practice. Although price differentiation helps capture unique market characteristics, it also encourages parallel trade, which may affect the overall corporate performance of a global company. We study this problem with a single global business unit (GBU) and multiple local business units (LBUs). The GBU manufactures a product and sets a transfer price for supplying the product to all LBUs, and LBUs decide retail prices for their respective regional markets. Customers can purchase products in any region by comparing LBUs’ prices and other parallel-imported factors, and we construct the demand by a mixed-multinomial logit model. Therefore, each LBU needs to consider the other LBUs’ prices when setting its price, and we formulate this problem as a two-stage game-theoretic model. We verify the existence of a pure-strategy Nash equilibrium. We then develop a learning-based algorithm to find the equilibrium prices of LBUs. Our algorithm is computationally efficient with a large scale of decision-makers. Even for cases with 100 decision-makers, the pure-strategy Nash equilibrium can be obtained within 30&#xa0;minutes. Numerical studies are conducted using data from the fast-moving consumer products industries. Although parallel trade is detrimental to some LBUs, the existence of parallel trade surprisingly leads to higher overall corporate profits, which is made possible by making the product available at different price points in a market. The proposed method also enables the quantitative validation of several conjectures on parallel trading practices.</p>