Applying Diffusion of Innovations Theory November 14, 2010 COM 126 K. Vook Once innovation occurs, innovations may be spread from the innovator to other individuals and groups. In 1962, Everett Rogers proposed that the life cycle of innovations can be described using the “s-curve” or diffusion curve. The s-curve maps growth of revenue or productivity against time.
In the early stage of a particular innovation, growth is relatively slow as the new product establishes itself. At some point consumer demand increases and product sales expand more rapidly.New incremental innovations or changes to the product allow growth to continue. Towards the end of its life cycle growth slows and may even begin to decline. In the later stages, no amount of new investment in that product will yield a normal rate of return.
Innovative companies will typically be constantly working on new innovations that will eventually replace older ones. Successive s-curves will come along to replace older ones and continue to drive growth upwards. In the figure above the first curve shows a current technology.The second shows an emerging technology that currently yields lower growth but will eventually overtake the current technology and lead to even greater levels of growth. The length of life will depend on many factors (DeFleur, M.
& Ball-Rokeach, S. (1989). The Bass diffusion model developed by Frank Bass in 1969 illustrates the process by which a new innovative product is adopted by new users, then is overtaken by products imitating the innovation. The model is widely used in forecasting, especially product forecasting and technology forecasting (DeFleur, M. & Ball-Rokeach, S.
1989). In the 1980s, Veneris (1984, 1990) developed a systems dynamics computer simulation model which takes into account business cycles and innovations. Innovation diffusion is studied by economists in a variety of contexts, for example in theories of entrepreneurship or in Paul Romer’s New Growth Theory (Haider, M. ;amp; Kreps, G. (2004). Success in implementing an innovation does not guarantee a beneficial outcome.
Research shows that from 50 to 90 percent of innovation projects are judged to have made little or no contribution to the goals of the innovating organization.Innovations that fail are often potentially ‘good’ ideas but do not achieve desired results because of budgetary constraints, lack of skills, poor leadership, lack of knowledge, lack of motivation, or poor fit with current goals. The impact of failure goes beyond the simple loss of investment. Failure can also lead to loss of morale among employees, an increase in cynicism and even higher resistance to change in the future. Most companies allow for the possibility of failure when planning an innovation, and include processes for detecting problems before they consume too many resources and threaten the organization’s future (DeFleur, M.
amp; Ball-Rokeach, S. (1989). Early detection of problems and adjustment of the innovation process contribute to the success of the final outcome.
The lessons learned from failure often reside longer in the organizational consciousness than lessons learned from success (Haider, M. ;amp; Kreps, G. (2004). Attempts to measure innovation take place on two levels: the organizational level and the political level. Within an organization, innovation can be evaluated by conducting surveys and workshops, consulting outside experts, or using internal benchmarks.
There is no measure of organizational innovation. Corporate measurements generally utilize scorecards which cover several aspects of innovation such as financial data, innovation process efficiency, employees’ contribution and motivation, and benefits for customers. The elements selected for these evaluations vary widely from company to company and may include new product revenue, amount spent on research and development, time to market, customer and employee perception and satisfaction, number of patents, and additional sales resulting from past innovations (DeFleur, M. & Ball-Rokeach, S. (1989).On a political level, measures of innovation are used to compare one country or region with another. The OECD (Organisation for Economic Co-operation and Development) Oslo Manual of 1995 suggested standard guidelines for measuring technological product and process innovation.
The new Oslo Manual of 2005, 3rd edition, added marketing and organizational innovation. The Bogota Manual was created in 2001 for Latin America and the Caribbean countries. A traditional indicator used to measure innovation is expenditure, for example, investment in R&D (Research and Development) as a percentage of GNP (Gross National Product). DeFleur, M. & Ball-Rokeach, S. (1989) Economists Christopher Freeman(born 1921) and Bengt-Ake Lundvall developed the National Innovation System (NIS) to explain the flow of technology and information which is key to the innovative process on the national level. According to innovation system theory, innovation and technology development are results of a complex set of relationships among people, enterprises, universities and government research institutes (Haider, M.
& Kreps, G. (2004).The 2008-2009 Global Innovation Index created by Soumitra Dutta, a professor at French business school INSEAD, along with New Delhi based non-profit organization “The Confederation of Indian Industry” ranks nations based on indices such as the number of internet users in a nation, the “ease of doing business,” and the stability of banks. Every factor is then categorized as either an input or an output. Inputs indicate how conducive countries are to fostering innovation, and include institutions and policies, human capacity, infrastructure, technological sophistication, business markets and capital.The outputs indicate how effectively countries translate innovation into benefits such as knowledge, competitiveness and wealth (DeFleur, M.
& Ball-Rokeach, S. (1989). Reference DeFleur, M. & Ball-Rokeach, S. (1989).
Theories of mass communication (5th ed. ). White Plains, NY: Longman. Haider, M. & Kreps, G. (2004).
Forty Years of Diffusion of Innovations: Utility and Value in Public Health. Journal of Health and Communication, 9. 3-11.