Pricing Access Services

Abstract

Many established industries, such as the online service industry, the telecommunication industry, or the fitness club industry, are access service industries. When using services in these industries, consumers pay for the privilege of accessing the firm's facilities but do not acquire any right to the facility itself. A firm's pricing decisions in access industries frequently come down to a simple choice among pricing, pricing, or pricing. However, it is not so simple for firms in those industries to make this choice. Access service firms typically face a mix of consumers who have intrinsically different usage rates. A key characteristic of access service firms, however, is that the cost of providing an additional minute of usage is typically negligible, as long as the firm has the necessary capacity to serve its customers. Service capacity, which corresponds to the total available time on a firm's system, is often limited. In this paper, we show that service capacity and consumer usage heterogeneity are two important factors that determine a firm's optimal choice. We develop a model that incorporates these two salient characteristics shared by access industries and study what determines a firm's choice among the three alternative pricing structures ( pricing, pricing, or pricing). Our analysis shows that, in the presence of consumer usage heterogeneity, service capacity mediates a firm's optimal choice in a complex, yet predictable way. A firm's choice also hinges on whether heavy or light users are more valuable in terms of their willingness-to-pay on a per-unit-capacity basis. The presence of both consumer usage heterogeneity and capacity constraints prompts a firm to choose its pricing structure to attract a desired customer mix and to price discriminate. As a result, two-part tariff pricing is not always optimal in access industries, and a firm's pricing structure can vary in a complex way with the interaction of those two factors. Specifically, we show that when light users are more valuable, a firm may use a two-part tariff or a flat fee, depending on whether the firm is constrained by its service capacity, but never charge a usage price alone or offer any signing bonus (a negative flat fee or a flat payment to customers). When heavy users are more valuable, a firm may choose to set a usage price, a signing bonus plus a usage price, or flat fee. Interestingly, regardless of whether heavy or light users are more valuable in an access service industry, only flat rate pricing is a sustainable pricing structure once the industry has developed sufficient excess capacity. We also show that the optimal pricing strategy in access industries can have some intriguing, nonintuitive implications that have not been explored elsewhere. For instance, when the industry capacity is unevenly distributed between competing firms, the large-capacity firm may well be advised to increase, rather than to decrease, its price to accommodate the small firm. It would be too costly and too tactless for the large firm to do otherwise. ...

Pricing of Software Services

“…8 That is, there is a value c such that g is strictly concave over subinterval [a, c) and strictly convex over (c, b]. To see this:…”

“…Jain et al(1999) develop a model for cellular phonecall prices and find the optimal pricing strategy over time. Essegaier et al(2002) compare two part tariffs with fixed-fee pricing and usage pricing for access service industries under conditions of customer usage heterogeneity and limited capacity. Danaher(2002) conducts a market experiment to compare different two part pricing packages for new subscription services.…”

Optimal Three-Part Tariff Plans

“…Essegaier et al (2002) computed the optimal two-part tariff plan under constraints on service capacity and heterogeneous consumer use. They assumed that usage rates of individual consumers vary, and that the marginal cost of serving a customer is low and independent of the consumers usage rate.…”

Competitive Behavior-Based Price Discrimination for Software Upgrades

“…Several mechanisms for price discrimination have been studied Information Systems Research 23(1), pp. 60-74, © 2012 INFORMS in the literature: Narasimhan (1984) study coupons, Terwiesch et al (2005) analyze a "name your own price channel," Essegaier et al (2002) look at nonlinear pricing schemes in the context of capacity constraints, Chen et al (2001) evaluate the impact of imperfect individual targetability on profits under competition, Van Ackere and Reyniers (1995) evaluate the optimality of conditioning prices on purchase history. Some researchers like Lu and Moorthy (2007) have compared the attractiveness of different mechanisms for price discrimination.…”