Pricing in the presence of strategic consumers

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Supply chain management strives to minimize supply-demand mismatch. This objective is constantly challenged by changing environments, risks, and uncertainties. Many Canadian businesses, such as those in the travel and hospitality industries, engage in multi-period competitive dynamic pricing, where demand modelling plays a major role. These dynamic pricing decisions are operationalized through revenue management mechanisms, often commanding frequent price updates. An outcome of revenue management algorithms is price volatility, which can influence consumers’ purchase and timing decisions in ways that have not been studied yet by the academic literature. The proposed research will assemble rich datasets, primarily from the airline industry, to analyze and enhance our knowledge on the emerging trade-offs in the presence of price volatility or revenue managed goods. Insights generated from the empirical analysis will serve as the foundation for analytical game-theoretical multi-period dynamic programming models, capturing demand more realistically: traditional revenue management models will be redesigned and extended to incorporate the effects of price volatility for varying degrees of competition intensity and strategic consumer behaviour to identify optimal levels of price updates and their magnitudes.