Technology forecasting: A case study of computational technologies

This research presents trend projection and technology maturity curve of six computational technologies including three disruptive technologies namely mainframes, minicomputers and cloud computing. This investigation is beneficial to sensitize different stakeholders for making effective strategic policies and decisions. Time series data of patent and paper from U.S. patent office, European patent office, IEEE and ScienceDirect is used for forecasting. Use of two technology indicators from four sources made the forecasting results more reliable for decision makers. Six functions are tested to identify the best-fitted trend line. Results indicate that most of the technologies are better fitted to polynomial trend line of 2nd order. All computational technologies except cloud computing have undergone both upward and downward trends. Cloud computing shows a very high upward trend. Maturity curve is forecasted using the best-fitted growth curve method. Gompertz growth curve is better fitted than the logistic curve for many instances. Majority of the technologies follows introduction, growth, maturity and decline pattern. The life cycle pattern and growth rate of each technology is different. Growth pattern of mainframes and minicomputers is similar to the S-shaped curve. Growth pattern of grid computing and autonomic computing is similar to the “S-shaped” curve for research papers dataset. •We examine life cycle of computational technologies.•Examined growth pattern of newer technologies such as cloud computing•Validated growth pattern of mainframes and minicomputers•Growth rate of new computational technologies is high.