An analysis of property-function based patent networks for strategic R&D planning in fast-moving industries: The case of silicon-based thin film solar cells

Patents are an up-to-date and reliable knowledge source of innovative technologies, and therefore patent analysis has been a vital tool for understanding technological trends and formulating technology strategies. One method of patent analysis is citation-based patent analysis. However, one criticism of the citation-based approach is that it may underestimate new patents because they tend to be less cited. This problem gets worse in fast-moving industries where technology life-cycles shorten and innovative technologies are actively patented. As a remedy, this paper proposes a property-function based patent network using an analysis of patent contents. Properties and functions as the innovation concepts of a system can be extracted using grammatical analysis of patent text. First, this paper represents each patent into a matrix codifying properties, functions and their co-occurrences, and then it constructs a patent network by measuring patent similarities. As a result, the proposed network reveals the internal relationships among patents in a given patent set that many new patents. Furthermore, using several analysis indices, this paper suggests a way to identify technological implications from the network such as the technological importance of new patents, the technological capability of applicants with new patents and the pace of technological progress of new patents. The proposed method is illustrated using silicon-based thin film solar cells. We expect that the proposed method can be incorporated into R&D planning processes to assist researchers and R&D policy makers to identify technological implications related to new patents in fast-moving industries. (C) 2012 Elsevier Ltd. All rights reserved.