Forecasting and evaluating emerging technologies based on supply and demand matching – a case study of China's gerontechnology.

While numerous studies have examined the importance of technology innovation in supporting the aging society, few have been specifically conducted on the emerging technologies that forecast for the elderly. Moreover, existing related research lacks consideration of public users' demands, and the forecasting results have not been linked with the actual technology supply in the market, which may easily lead to waste of resources and deviation of R&D focus. Given that, we present a novel method to forecast and evaluate emerging technologies based on technology supply and demand (S&D) matching. In the case study of China's gerontechnology, we first systematically excavate the elderly's demands and match them with the emerging gerontechnologies. Then, we analyse technology supply to filter out S&D oversaturated technologies and screen out S&D undersaturated results by the text semantic mining and similarity matching. Among the results, 27.68% do not have an effective supply yet, 33.04% have saturated or oversaturated. Besides, we use the TRIZ theory to filtrate key emerging areas and find the evolution path, and six significant evolutionary trends are extracted. This paper will help decision makers to accurately target the most promising emerging technologies. Highlights A framework to forecast emerging technology based on supply and demand match. Considering aging population in the technology forecasting and foresight. Monitoring emerging technology trends by using social user's demands analysis. 75 emerging technologies and 6 evolution trends of China's gerontechnology. Filter out 33.04% supply saturated and oversaturated of forecasted results. [ABSTRACT FROM AUTHOR]