Determining Technology Life Cycle Prediction based on Patent Bibliometric Data

Abstract

The primary purpose of the present study is to determine the life cycle and technology prediction based on patent bibliometric data using Markov hidden model. The study population included 50,915 patent licenses in medical equipment extracted from the US Patent and Trademark Office database from 1976 to 2015. The study findings revealed technology life cycle patterns in 21 medical equipment sub-areas. The status of medical device patent license indicators at different stages of the technology life cycle, alongside the likelihood of state transfer at different stages of the medical technology life cycle, were investigated. Ultimately, the results showed that "Drug delivery equipment, Disposable medical equipment, Oximeters, and Sharps (Medical instruments)" have more suitable areas for investment and commercialization. The current research results can also provide a good insight into technologies and can be used as a guide alongside experts and other decision-making methods.

Keywords

• technology forecasting
• technology life cycle
• patents
• hidden markov model
• medical equipment