Promotion Strategy for a Service Firm with Delay Sensitive Customers
61 Pages Posted: 13 Dec 2016 Last revised: 15 Dec 2018
Date Written: June 27, 2016
Online social advertising tools such as Groupon and Living Social generate new business for service providers and at the same time generate new challenges. By doing promotion, a ﬁrm may unavoidably attract deal hunters who are less likely to continue to purchase the service after promotion. Even worse, those discount-seeking customers may impose externalities on the system that could drive away regular customers. This paper considers a promotion strategy for a service ﬁrm faced with customers who are delay sensitive. We study the equilibrium behavior of such a system and analyze the trade-o˙s of promotion. We ﬁnd that a service ﬁrm beneﬁts from a promotion only when the average waiting time without promotion is low. We devise recommendations regarding when promotions would be beneﬁcial: promotion is more likely to be proﬁtable for a ﬁrm with a small market size and high prices. In order to characterize the optimal promotion strategy, we derive approximations of such a system that turn out to be extremely accurate to the optimal solution. Using the approximation, we ﬁnd that when the price is endogenous, the optimal promotion strategy may arise in two different operations regimes depending on the future discounting factor. If the future discounting factor is large, the system is overloaded in the promotion period and critical loaded in the post-promotion period. If the future discounting factor is small, the system is critical loaded in the promotion period and underloaded in the post-promotion period. When the promotion and price decisions are made jointly, the overloaded promotion strategy is more likely to arise. In addition, promotion size and price are complements in the second order reﬁnement problem. The empirical analysis based on a combination of google business traffic dataset and Yelp academic dataset veriﬁes the main ﬁndings in the theoretical analysis.
Keywords: Online Social Promotion, Economics of Queues, Delay Sensitive Customers, Large Market Approximation, Empirical Analysis
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