This paper proposes price cannibalization as a growth strategy despite prior findings in avoiding it. We focus on a multi-class, capacity-constrained pricing problem in which each of the product classes has a price range. Specifically, we examine the effects of price range overlaps and introduce it as a revenue-maximizing pricing strategy that enables better capacity utilization. Price cannibalization happens when sales in some product classes decrease due to the existence of overlaps between the price ranges. This research employs a multi-method approach. First, we define a Markovian Decision Problem (MDP) to obtain the revenue-maximizing pricing strategy in a two-class sales scenario. We show that price range overlaps are part of the optimal strategy. Second, we collect multichannel data from a European storage company to examine how price range overlaps impacts a customer’s purchase decisions. Our empirical results show that the existence of price range overlaps increases customer spending and improves conversion. Finally, we use simulations to compare several pricing strategies and demonstrate the long-term effects of using price range overlaps as part of a pricing algorithm in complex situations. Our findings suggest that using price range overlaps, though leads to cannibalization, actually helps companies avoid spoilage and early sell-outs, leading to better capacity utilization and higher revenue. We discuss the theoretical and managerial implications of our findings.
|Publication status||Published - 2022|