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Under technology convergence phenomenon and fast-changing social demands, it is inevitable to collect and analyze a large amount of information in order to determine a vacant technology area that can preempt the market. Thus, this research aims to propose a systematic approach to identifying vacant technology areas by reflecting the technological competitiveness of company. Vacant technology is identified as underdeveloped and undeveloped vacant areas for a firm in both macroscopic and microscopic view by generating a technology level map in a practical view. In addition, vacant technology can be identified as undiscovered vacant areas in a microscopic view by using generative topology mapping (GTM) and local outlier factor (LOF). In a respective view, the promising vacant areas are defined by developing various indicators that represent competitive strength, growth stage, and marketability in both macro and micro level, and novelty indicators that represent originality and marketability in the micro level. The proposed approach is applied to the information & communication technology (ICT) R&D technology classification to validate its usefulness. The results can be used to enhance the practical application of R&D technology planning, understand the current technology level, and perform future technology planning. [ABSTRACT FROM AUTHOR]

Under technology convergence phenomenon and fast-changing social demands, it is inevitable to collect and analyze a large amount of information in order to determine a vacant technology area that can preempt the market. Thus, this research aims to propose a systematic approach to identifying vacant technology areas by reflecting the technological competitiveness of company. Vacant technology is identified as underdeveloped and undeveloped vacant areas for a firm in both macroscopic and microscopic view by generating a technology level map in a practical view. In addition, vacant technology can be identified as undiscovered vacant areas in a microscopic view by using generative topology mapping (GTM) and local outlier factor (LOF). In a respective view, the promising vacant areas are defined by developing various indicators that represent competitive strength, growth stage, and marketability in both macro and micro level, and novelty indicators that represent originality and marketability in the micro level. The proposed approach is applied to the information & communication technology (ICT) R&D technology classification to validate its usefulness. The results can be used to enhance the practical application of R&D technology planning, understand the current technology level, and perform future technology planning. [ABSTRACT FROM AUTHOR]

The aim of the present research is to provide a new systematic methodology to explore potential Research and Development (R&D) collaboration partners using patent information. The potential R&D collaboration partners are visualised as a patent assignee level map based on technological similarity between patents by using the network analysis. The proposed framework utilises two analytic methods to measure technological similarity. The first method, bibliographic coupling analysis, measures technological similarity based on the citation relationship using patent bibliographic information. Second, latent semantic analysis is utilised based on semantic similarity using patent textual information. The fuel cell membrane electrode assembly technology field is selected and applied to illustrate the proposed methodology. The proposed approach allows firms, universities, research institutes and governments to identify potential R&D collaborators as a systematic decision-making support tool. [ABSTRACT FROM PUBLISHER]