A Study of Market Scale and Share Estimation Methodology on Effective Feasibility Analysis of IT R & D Program Using Fuzzy & Big Data

Standardizing the various benefits and performance features of the different government R & D programs is difficult. This is largely because each of them involves a wide variety of necessary research. In order to minimize benefit distinctions--the difference in benefit between the proposal and the alternative--the OECD benefit assessment report was examined. Associated Research results and benefit distinctions from preliminary feasibility data were also used to draw benefit estimation hindrance factors. Analytic Hierarchy Process is used to identify the relative importance rank of benefit estimation hindrance factors. If Independence between benefit estimation hindrance factors fails to satisfy the evaluation criteria then, a model based on the fuzzy measure is applied. This is for drawing optimal evaluation results, In order to know the correlation between benefit distinctions and benefit estimation hindrance factors ordered digit model is utilized. The application of big data technique is used as a means to collect extensive trend data and adequately capture technology trends. In this paper, the R & D program related to Information Technology was classified into four categories (First-mover, Catch-up, Data existence). Finally a methodology for extracting a relevant market scale and a market share data is proposed.