Abstract
Patents play a crucial role in determining the economy, industrial development, and R&D of a country. Extant patent literature has focussed on the decision model of the econometric method, which enables researchers to understand the short-term explanatory power of various factors for patent value. However, this method cannot be used to observe the degradation rate and growth trajectory of the patent value. In this study, we proposed a dynamic time-series design to further explore the growth trajectory of patent value by using the latent growth curve model. The results show that backward citation, non-patent reference, and number of claims positively affect the patent value growth rate. Patent disclosure information and characteristics are crucial for exploring the value of patents. Patent value is typically established on the basis of knowledge stock, patent breadth and international linkage. Therefore, this study applied an experimental map to validate the linkage relationship of the studied dimensions to provide governments, industries and patent assignees with some practical suggestions.
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