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Wieden and Kennedy Essay

This article is partitioned into three parts which is summarized here. First, different kinds of platform structures are introduced. Then the most important part, which we will use later in order to analyze the Google study case, is dealt with the influencing factors on the so called structures. In the end there is shown a framework so that to analyze the factors mentioned in the previous section. By definition platforms are subset of components and rules employed by users in most of their transactions. Components include hardware, software, and services while the rules are combinations of technical standard, protocols for information exchange, policies, and contracts that govern transactions. We can conclude this paragraph only by looking at the figure below. Recall here in this article we focus on two-sided networks, since they are the most typical platform-mediated network. Two-sided networks, are economic platforms having two distinct user groups that provide each other with network benefits.

There are three different kinds of platform structure, named Multi-Homing, Mono-Homing, Mixed-Mode Homing, and Winner-Take-All (WTA). Here we focus on WTA platform structure in which one platform serves the mature, say saturated, networked market; roughly speaking, over 90% of the relevant networked market. There are different factors influencing platform structures, numbered as:

1. Whether the market is a “natural monopoly”
2. Multi-homing costs
3. The strength of network effects
4. User’s preferences for differentiated platform functionality Looking at the platform structure, one should consider a combination of these factors; they are not isolated and cannot be analyzed as separate factors. Minimum efficient scale beyond the extent of mature market size defines a “natural monopoly”. Multi-homing is a circumstance in which two-sided markets contain more than one competing platform. The network may have positive or negative effects itself, for instance if communicating with other users is not valued equally, then accessing to others may have negative effects, on the other hand if the users value the ability to interact with large numbers of other users, then it is more probable that the network served by a single platform, it is the case of positive effects. Platform differentiation concerns with the fact of using multiple platforms, in contrast with the case of single platform when users have relatively homogeneous needs, with different preferences.

As a framework for analysis the factors mentioned above, there are different scenarios which are the combinations of the influencing factors. It is assumed that cross-side network effects are positive in both directions, and same-side network effects on both sides are either neutral or positive. We also assume that network users cannot influence platform structure. Based on these assumptions there are different scenarios for variety of platform structures. For the case of WTA there are two scenarios. One is related to the case of high multi-homing costs on both sides, strong preference for transaction partner variety on at least one side, and neither side has a strong preference for differentiated platform functionality. The second scenario is conditioned by high multi-homing costs on only one side, which exhibits a strong preference for transaction partner variety, and neither side has a strong preference regarding differentiated platform functionality.

In the case of Mono-homing platform structure, which is on one side of a two-sided market while the other side a multi-homing case. The mono-homing side is constrained with high multi-homing costs and has a strong preference for differentiated platform functionality that cannot be offered selectively, meanwhile the multi-homing side has low multi-homing costs and has a strong preference for transaction partner variety. And finally in the mixed-mode condition, some users on each side mono-home due to a strong preference for differentiated platform functionality-typically transaction-specific-and a relatively weaker preference for transaction-partner variety. The remaining users on each side multi-home due to a stronger preference for variety.

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