However, many different theorists all ave different beliefs in why innovations diffuse within a given society.
One of the theories available is the theory of advanced diffusion due to geographical cluster by Rui Baptista (2000). This theory states that "geographical proximity of innovators and early adopters stimulates networking between firms, thereby facilitating imitation and improvement" (Baptista, p 516, 2000). This theory also looks at how network cohesiveness is positively related to the degree of innovative success (Baptista, p 517, 2000).Thus, close proximity not only allows for competitors to think up new nnovative ideas and how to further enhance their existing product line, it practically forces them to do so because the rate of entry and competition is so high that failure to stay ahead of the innovation curve will lead to a company shutdown, and in turn, increases the overall industry and market in the process. Another theory that exists to help explain how innovations diffuse is the theory of the role of hubs in the adoption process (Goldenberg, p 1, 2009).
Hubs are people with many social ties and the earlier the hub adopts a new technology or product the same will be said for eople who know the hub or who are influenced by him/her (Goldenberg, p 3, 2009). However, a unique factor about this theory is that the hub himself/herself does not necessarily need to be an innovator for the product to diffuse. The fact that the hub is connected to so many different people, someone to whom he or she is connected to may have an innovative spirit or idea and could decide to adopt the new product being offered.An additional theory that exists in the world of marketing that theorists use to explain why innovations diffuse is the effect that online communities ave on society and the rate of adoption by a society (Hemetsberger, p 339, 2008).
Online communities are an integral part of the whole adoption process of an innovation because "they are often a source of ideas and inspiration for new product developments, Von Hippel (2005) states that over 10 to 40 perfect of users actually consent that they develop and modify products in fields of studied to date (Hemetsberger, p. 339, 2008)".Thus one can argue that if a product is successful online then it is a matter of time before it explodes into stardom within our society. Although all of the previous 3 theories have different focus points on why innovations diffuse, they all agree on the same 5 qualities that Les Robinson (2009) states a product must have to be successful. These are: Relative Advantage, Compatibility with existing values and practices, simplicity and ease of use, triability and observable results.
Thus, one can argue that a definite answer for why innovations diffuse may truly never be reached. . 2 Who are the Innovators? In regards to the literature available, many different theorists and diffusion have adamant believer that everyone who contributes to competition within a given ndustry is an innovator by simply pushing every other competitor to be that much better. On the other hand, Hemetsberger (2008) truly believes that online communities are the innovators in society through their social communication capabilities and the overall ease of access by the masses to the new technologies and products.
Additionally, Goldenbergs (2009) theory of the role of hubs clearly identifies two different types of producers that can innovate a product and help diffuse it. The first being the hubs themselves because if they adopt a new product or technology hen those influenced will undoubtedly follow, and the second are the fact that the hubs serve as platforms to introduce new products and technologies into society and thus allowing others the opportunity of innovating a new product and adopting it.Even though all the different theories look at producers in a different manner they all agree that they are the innovators of new products. They are the ones either through competition, online communities or hubs that continue to push through new inventions and products, and they are the ones who keep society advancing into unknown markets and ideas.
However, all scholars also believe that end users are also innovators because ultimately they are the ones who either reject or accept a product (Von Hippel, 2005). There are no typical end users, everyone is an end user and it all depends on the product being sold.BlackBerry, for example; which is the product our group is focusing on, has evolved from a corporate social tool to a device that is used by executives, parents, students and elderly alike. The end users accepted it and allowed it to evolve into the phenomena it is today. 3.
3 Length of Process of Diffusion / Similar Products Determining the length of the process of diffusion is a very hard task. Even though we cannot tell how long it will take an innovation to diffuse, theorists have attempted to discover what variables truly accelerate the process and which ones we assume to accelerate the process.Goldenberg (2009) tried to find out if hubs truly do accelerate the speed of adoption within a society. He discovered that at a neighbourhood level, hubs accelerate the adoption process substantially (Goldenberg, p 8, 2009).
During an experiment in which a company would give hubs a new product to show off, the nvestigators realized within a few days the entire community was already on the path to adopting the new technologies as well (Goldenberg, p 9, 2009). Furthermore, Baptista (2000) argues that the faster larger firms adopt a new innovation, the faster it will take the rest of the market to increase their competitive position.Thus, one can argue that even though one cannot predict the length of time of the diffusion process, variables such as large firm adoption, hub adoption, profitability condition, and arbitrage condition, undoubtedly will lead to an invention to diffuse much faster. During my research, the theorists that I studied did not use any products that are similar to ours which is the BlackBerry.
Goldenberg (2009) and Hemetsberger (2008) both used social networks and networking sites for experiments, while Baptista (2000) used computer machine tools and microprocessors for his experiments.
