Second, by bundling products a seller can reveal information on the use and benefits of these products. Even when this informational bundle value does not immediately translate into higher bundle reservation prices, it may — over time — lift up consumers’ valuation of the separate products. Research on the implications for (dynamic) product and bundle pricing seems warranted. A third dynamic demand effect that may favor bundling involves network externalities (Katz and Shapiro 1986). Network externalities imply that products become more valuable when more consumers have them (e.
g. , cellular phones).
Provided that bundling accelerates the penetration of a product, it can exploit network externalities more effectively than other strategies. More rigorous work is needed that throws light on the underlying mechanisms. Finally, in a dynamic context and under very specific conditions, bundling can be an effective rationing device. This is demonstrated by DeGraba and Mohammed (1999) for a two-product monopolist operating under a capacity constraint, the only formal dynamic bundling analysis we know of.
In a first period the monopolist implements a pure bundling strategy and sets the bundle price such that only high value consumers, expecting a shortage in the next period (due to the capacity constraint), purchase the bundle. In the second period the seller offers the (remaining) products only unbundled, at prices that allow to maximally extract the surplus of low value buyers. DeGraba and Mohammed call this two-period-strategy “intertemporal mixed bundling”.
First, bundling can be effective in generating future cost advantages. As a bundle yields higher sales volumes, marginal costs (which until now were assumed constant over time) may decrease due to learning effects in production and distribution, allowing higher profit margins.
Second, multi-product sellers should account for dynamics in the competitive environment. Though never really modeled as such, the extension of monopoly power is essentially a dynamic phenomenon as it is based on a seller’s ability to anticipate his rival’s reaction.
A duopolist’s bundling strategy may not be rewarding initially, yet may become so once the rival is driven out of business. Similarly, a monopolist’s bundling strategy may be suboptimal in the short run, yet may discourage potential entrants in the long run and thereby avoid a dramatic fall in profits (Bakos and Brynjolfsson 2000). Conclusion According to Shapiro and Varian’s (1999) work, computer and communications infrastructure or data networks (e. g. , the Internet) might make it possible for today’s entrepreneurs dealing in information goods to build new monopolies (e. g. , Microsoft).
Since the marginal cost of reproducing these goods has been considerably reduced and those entrepreneurs can take advantage of unprecedented economies of scale (both permitted nowadays by computer and communications infrastructure), information goods producers have been regarding bundled sales as a powerful and attractive pricing strategy. Based on differences in consumers’ valuations over bundles of information goods, this strategy makes it possible for those producers to extract more revenue from consumers.
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