Online Auctions and Multichannel Retailing

The Internet enables sellers to offer products through multiple channels simultaneously. In particular, many sellers utilize online auctions in parallel to other online and offline channels. Using an analytical model and data from eBay Motors, we study seller behavior and auction outcomes in the context of multichannel retailing. Our model shows that seller characteristics which affect the distribution and volume of offers in the non-auction channels impact the probability an auction ends in a sale, the probability an item is sold through the auction channel, and the sale price in case of a sale. The impact on the two probabilities can be negative or positive and depends on whether the seller manages the channels jointly or separately. Our empirical analysis examines how the quality of the seller’s retail location and her electronic commerce capabilities (i.e., two seller characteristics influencing demand in non-auction channels) impact the auction channel outcomes. The results confirm the joint channel management strategy considered in the analytical model.http://deepblue.lib.umich.edu/bitstream/2027.42/92349/1/1176_Etzion.pd

Pricing of Products and Complementary Services: A Study of the Online Game Industry

We model a monopolist who offers a product and a complementary service, where only the latter exhibits positive network externalities. We focus on the online game industry as a representative case in which the product (the game), unlike the service (access to the interactive online play mode), has zero marginal cost, and consider two-potential pricing strategies: 1) the bundle pricing, in which the vendor charges a single price for the product and the service; and 2) the separate pricing, in which the vendor sets the prices of the product and the service separately. We find that, in contrast to the common result in the bundling literature, bundling may increase consumer surplus, while the monopolist chooses not to offer the bundle. We offer theoretical evidence that this is due to the presence of network externalities

Complementary Online Services in Competitive Markets: Maintaining Profitability in the Presence of Network Effects

A growing number of firms are strategically utilizing information technology and the Internet to provide online services to consumers who buy their products. Online services differ from traditional services because they often promote interactivity among users and exhibit positive network effects. While the service increases the value obtained by consumers, network effects are known to intensify price competition and thus may reduce firms’ profits. In this paper, we model the competition between two firms that sell a differentiated product when each firm can offer a complementary online service to its customers. We derive the market equilibrium and determine how firms should adjust their strategies to account for network effects. We find that when the service exhibits network effects, a firm’s decision whether or not to offer the service depends on both the competitor’s decision and the competitor’s service quality. When the service does not exhibit network effects, this is not the case. In addition, we show that a firm can benefit from the technological ability to offer the service, and from an increase in the strength of network effects or in the market size of the service, only when the value customers derive from the direct functionalities (those that do not rely on the network) of the service are sufficiently high. As a result, a firm’s investment in the direct functionalities of its service increases with the strength of network effects of the service as long as the marginal development cost is not too high. Finally, we show that inefficiencies in terms of the number of firms offering the service as well as the total number of service users may prevail

Appendix A Derivations of Equilibrium Prices and Profits per Market Configuration Configuration

We derive the equilibrium in prices and demands given the choices of the two firms in the first stage of the game. We consider only cases in which (1) each firm has positive demand for its product, and (2) market is covered. The required conditions on the parameters values are given in the following assumption. Assumption 1. Conditions for Spatial Competition in Equilibrium (i) 2t> M(α A + α B), where α i = 0 when firm i does not offer service (A1) (ii) c – 3t + α IM – Δ i < s i < 3t – 2α iM + c – Δ i (i, j = A and B, i … j) (A2) (iii) –3t + M(αi + 2αi) – Δi < si – sj < 3t – M(2αi + αj) – Δi (iv) |mi – mj | < 3t (v) 3t+ mA+ mB ( 2 SN NS SS) V> max, V, V,

Asymmetric Competition in B2B Spot Markets

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74465/1/poms.1080.0014.pd