Planning and Forecasting

Planning and Forecasting

Technological forecasting has become the specific orderliness in terms of the innovation process. Studies on the technological transfer, diffusion, and substitution processes have resulted in conceptual models of successful innovation concepts. The innovative forecast plays a key role in the limited empirical measures separated from the other innovation models. The combination of the Bibliometric measures acts as the evidence that provides the enriched form of the innovative forecasting. This also provides a good means which combine the technological trends, competitive intelligence, and mapping of the technological interdependencies. The technological forecast will be providing timely insight right into the prospects needed for the crucial technological change. This kind of data will be helpful to the management in making better decisions in respect to the product development, production, R & D Management, strategic corporate planning, purchase of new technology, and the investment made in the new process technology. Technological forecasting has mainly encompassed different approaches, time horizons, and objectives (Watts & Porter, 1997).

The attempted technological innovation might be or might not be successful. The successful innovation would be relying upon different variables that include the technological characteristics, and it fits right between the technology and the technology firm, market forces, socio-economic factors, the familiarity of the firm with the related infrastructure and market, the economic resource and climate commitments, and the institutional interactions or actions. The innovation forecasting mainly extends with the traditional monitoring through tapping the electronic information resources that are newly found. The information in the given technology will be bound on the electronic and internet databases. Emphasizing the data has begun structuring and screened. The World Wide Web has been providing access towards the present and varied sources. The retrieval tools and the intelligent search will be improving the web that becomes a valuable source for monitoring the technology. 

The technological life cycle information acts as the key for determining how the development pathway gets advanced with the growth rate and the status of the technologies, which is quite dependent. The contextual factors would be included with the economic influences upon the development of the target technology. The growth rate could be ascertained through the general technology or by contributing the technologies over the item counts. This could combine with the R&D profile by plotting the number of hits per year. The trend models could be fitted with the Bibliometric time series data. The examination of the raw frequencies could be quite informative (Landau, 2018). 

 



References

Landau, P. (2018). Business Forecasting: Why You Need It & How to Do It. Retrieved from, https://www.projectmanager.com/blog/business-forecasting

Watts, R. J. & Porter, A. L. (1997). Innovation Forecasting. Retrieved from, https://www.researchgate.net/publication/3709830_Innovation_Forecasting

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