Intellectual property research and development (IP R&D) is an essential condition in order to be more competitive in the rapidly changing global market environment. The ultimate objective of IP R&D is technology forecasting. Technology forecasting (TF) attempts to discover the future state of a technology. Many quantitative and qualitative TF-related research efforts currently exist. Expert survey is a qualitative forecasting method; expert survey technology forecasting (ESTF) is one of many TF methods. The goal of ESTF is to predict the future state of a target technology using expert survey. Although ESTF has many advantages, it is less stable than other quantitative TF methods such as patent analysis because ESTF is subjectively based on the knowledge of experts. It is obvious that quantitative approaches such as patent analysis also have limitations. One of these limitations is the need for the experience of domain experts for the interpretation of patent analysis results. In this paper we propose a patent analysis approach that improves the performance of ESTF. Our approach combines patent analysis with the expert survey forecasting method to improve the predictive effectiveness of ESTF. The efficacy of our approach is demonstrated by means of a case study involving TF work related to web survey technology.
Sunghae Jun, Seung-Joo Lee, Jea-Bok Ryu and Sangsung Park
Gabjo Kim, Yung Kim, Gyungtae Song, Dongju Sun and Sangsung Park
This study proposes a method for establishing an R&D strategy that can be used by R&D decision-makers in companies and countries in the display industry in order to develop an effective technology. In order to develop a technology tree for the display industry, the entire technology is classified into three main category levels (LCD, FD, and OLED), 19 subcategory levels, and 69 sub-subcategory levels, based on the opinions of the experts in the display industry and on the reports from related technologies. Next, the technology area is examined by conducting a patent indicator analysis on each of the 69 sub-subcategory levels and the technological life cycle is identified by applying the Bass diffusion model. Based on the results, we propose R&D strategies for decision-makers in the display industry, such as R&D investment, technology M&A, and monitoring strategy proposals.