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Adoption of Communication Products and the Individual Critical Mass - CHARACTERISTICS OF NETWORK EFFECTS, CONCLUSION

base installed function figure

Markus Voeth
University of Hohenheim, Germany

Marcus Liehr
University of Hohenheim, Germany


Generally, two dimensions of the emergence of direct network effects are distinguished (Shy, 2001). On the one hand, network effects arise in the framework of active communication, that is, when contacting an individual in order to communicate with him or her. On the other hand, network effects also result from the possibility of being contacted by other individuals (passive communication). As direct network effects therefore result from the possibility of interacting with other users, they do not automatically arise from the purchase of a product, but rather from its use.

Regarding the functional correlation between network effects and the installed base, the literature especially distinguishes the four functional types presented in Figure 1 (Swann, 2002). While the linear function (Figure 1a) stands for the assumption that regardless of the point of time of the adoption, each new adopter causes network effects to the same degree, the convex function (Figure 1b) represents the assumption that each later adopter causes higher additional network effects than earlier adopters. Those two types of functions commonly represent the assumption that network effects are indefinitely increasing in a social system. In contrast to this, the concave and the s -shaped functions express the assumption that network effects are limited by a saturation level. However, while in the case of a concave function (Figure 1c) every later adopter causes lower additional network effects than earlier adopters, the s -shaped function (Figure 1d) is a mixture of the convex function with a low installed base and the concave function with a higher installed base. As the problem of the functional relationship between network effects and the installed base has not received much attention in the literature, there is no clear indication on the real relationship.

In reference to the network effects’ dependency on the number of users, An and Kiefer (1995) differentiate between network effects that depend on the worldwide installed base (global network effects) and networks effects that depend on the number of neighbouring users (local network effects). However, the abstraction from the identity of the users of a communication product often proves inadequate when practical questions are tackled (Rohlfs, 1974). As communication products serve the satisfaction of communicational needs, network effects naturally depend on the form of an individual’s communication network. When deciding about the adoption of a camera cell phone, for example, people create high network effects with whom the potential adopter wants to exchange photos or videos. Therefore, it can be assumed that the adoption of people with whom the individual communicates more often or more intensively creates higher network effects than the adoption of people with a lower frequency or intensity of communication. Furthermore, groups of individuals exist, each of which display a similar communication frequency and intensity regarding the individual, thus making it necessary to differentiate between groups characterized by similarly high network effects for the individual (Voeth & Liehr, 2004).


The adoption of communication products is determined by the installed base and the network effects resulting from it. In order to derive marketing activities for communication products, it is therefore necessary to gather information about the characteristics of network effects and the level of the installed base, which is necessary in order to make an individual willing to adopt a communication product.

Based on the measurement of the individual critical mass, it is possible to determine the profitability of marketing measures for communication products. For example, if the start-up problem of a communication product is to be solved by giving away the product to selected persons in the launch period, it is not advisable to choose individuals with a low individual critical mass. Instead, it is recommendable to give the product to persons with a high individual critical mass. This is due to the fact that persons with a low individual critical mass would adopt the communication product shortly after the launch anyway, while persons with a high individual critical mass would adopt—if at all—at a much later date. Against this background, the measuring of the individual critical mass is highly relevant for the marketing of communication products.


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