Method and Empirical Investigation of Forecasting Technology Opportunity with Time-Series Patent Data
Lee Dongmei1, Song Zhihong 2
1.School of Mathematical Sciences,Shanxi University,Taiyuan 030006,China;
2.Institute of Management and Decision,Shanxi University,Taiyuan 030006,China
Abstract：The paper provides an Markov Regime-Switching model for forecasting technology opportunity with time-series patent data from January 1977 to June 2014 in semiconductor industry.The empirical results indicate that the transition between expansion state and contraction state of authorized patent quantity is relatively quick,and that the duration of an expansion state which authorized patent quantity is increasing significantly shorter than that of a contraction state in semiconductor industry.The average duration of an expansion state is about 4.167 months,while the average duration of a contraction state is about 13.699 months.Compared with previous studies,the Markov Regime-Switching(MRS)method in this paper provides a more accurate forecast on windows of technology opportunity in a specific field
李冬梅,宋志红. 基于专利时序数据预测技术机会的方法与实证研究[J]. 中国科技论坛, 2015(12): 39-44.
Lee Dongmei, Song Zhihong. Method and Empirical Investigation of Forecasting Technology Opportunity with Time-Series Patent Data. , 2015(12): 39-44.
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