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Theories Related to Vertical Software Industry Evolution

  • Lauri Frank
Chapter
Part of the Contributions to Management Science book series (MANAGEMENT SC.)

Abstract

The word innovation often refers to a new product, usually to an industrial or technical invention, although actually all kinds of new ideas should be considered. Following Rogers (2003, p. 12), “[a]n innovation is an idea, practice, or object that is perceived as new by an individual or other unit of adoption.” The birth of a new industry can be considered to occur as this new innovation is introduced to the markets by the first manufacturing firm. At this point the potential customers evaluate whether it is worth to adopt the product or not.

Innovation diffusion theory studies the spread of an innovation within a social system (see, e.g., Rogers 2003). The basic aim is to answer the question of why an innovation – an improvement – is not adopted immediately, i.e., why its diffusion takes time. One of the common answers is that not everyone knows of the innovation right away, others add, for example, that gained advantages or profits vary between potential adopters.

There are several dichotomous classifications of innovations, trying to separate innovations into two categories by their nature. Some of such dichotomous divisions are, for example, the division of innovations into incremental and radical innovations (e.g., Freeman 1994), into sustaining and disruptive (e.g., Bower and Christensen 1995), or into continuous and discontinuous innovations (e.g., Tushman and Anderson 1986). Even though the category names differ, these divisions seem to have the same basic aim: An innovation may be a totally new innovation (e.g., product), but it also could be an improvement to an existing innovation. In practice, however, it is often hard to place an innovation into one of these two categories as it might have some characteristics from both.

Keywords

Network Externality Potential Adopter Vertical Specialization Computer Industry Startup Size 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Computer Science and ISUniversity of JyväskyläJyväskyläFinland

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