TY - JOUR A1 - Schlosser, Rainer T1 - Stochastic dynamic pricing and advertising in isoelastic oligopoly models JF - European Journal of Operational Research N2 - In this paper, we analyze stochastic dynamic pricing and advertising differential games in special oligopoly markets with constant price and advertising elasticity. We consider the sale of perishable as well as durable goods and include adoption effects in the demand. Based on a unique stochastic feedback Nash equilibrium, we derive closed-form solution formulas of the value functions and the optimal feedback policies of all competing firms. Efficient simulation techniques are used to evaluate optimally controlled sales processes over time. This way, the evolution of optimal controls as well as the firms’ profit distributions are analyzed. Moreover, we are able to compare feedback solutions of the stochastic model with its deterministic counterpart. We show that the market power of the competing firms is exactly the same as in the deterministic version of the model. Further, we discover two fundamental effects that determine the relation between both models. First, the volatility in demand results in a decline of expected profits compared to the deterministic model. Second, we find that saturation effects in demand have an opposite character. We show that the second effect can be strong enough to either exactly balance or even overcompensate the first one. As a result we are able to identify cases in which feedback solutions of the deterministic model provide useful approximations of solutions of the stochastic model. KW - Pricing KW - Advertising KW - Stochastic differential games KW - Oligopoly competition KW - Adoption effects Y1 - 2017 U6 - https://doi.org/10.1016/j.ejor.2016.11.021 SN - 0377-2217 SN - 1872-6860 VL - 259 SP - 1144 EP - 1155 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schlosser, Rainer A1 - Boissier, Martin T1 - Dealing with the dimensionality curse in dynamic pricing competition BT - Using frequent repricing to compensate imperfect market anticipations JF - Computers & Operations Research N2 - Most sales applications are characterized by competition and limited demand information. For successful pricing strategies, frequent price adjustments as well as anticipation of market dynamics are crucial. Both effects are challenging as competitive markets are complex and computations of optimized pricing adjustments can be time-consuming. We analyze stochastic dynamic pricing models under oligopoly competition for the sale of perishable goods. To circumvent the curse of dimensionality, we propose a heuristic approach to efficiently compute price adjustments. To demonstrate our strategy’s applicability even if the number of competitors is large and their strategies are unknown, we consider different competitive settings in which competitors frequently and strategically adjust their prices. For all settings, we verify that our heuristic strategy yields promising results. We compare the performance of our heuristic against upper bounds, which are obtained by optimal strategies that take advantage of perfect price anticipations. We find that price adjustment frequencies can have a larger impact on expected profits than price anticipations. Finally, our approach has been applied on Amazon for the sale of used books. We have used a seller’s historical market data to calibrate our model. Sales results show that our data-driven strategy outperforms the rule-based strategy of an experienced seller by a profit increase of more than 20%. KW - Dynamic pricing KW - Oligopoly competition KW - Dynamic programming KW - Data-driven strategies KW - E-commerce Y1 - 2018 U6 - https://doi.org/10.1016/j.cor.2018.07.011 SN - 0305-0548 SN - 1873-765X VL - 100 SP - 26 EP - 42 PB - Elsevier CY - Oxford ER -