• Title/Summary/Keyword: Emerging Technology Demand Forecast

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A Study on the Demand Forecasting of Healthcare Technology from a Consumer Perspective : Using Social Data and ARIMA Model Approach (소셜데이터 및 ARIMA 분석을 활용한 소비자 관점의 헬스케어 기술수요 예측 연구)

  • Yang, Dong Won;Lee, Zoon Ky
    • Journal of Information Technology Services
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    • v.19 no.4
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    • pp.49-61
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    • 2020
  • Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

Development of Information Technology for Smart Defense (Smart Defense 를 위한 IT 기술 개발)

  • Chung, Kyo-Il;Lee, So Yeon;Park, Sangjoon;Park, Jonghyun;Han, Sang-Cheol
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.38 no.3
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    • pp.323-328
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    • 2014
  • Recently, there has been demand for the convergence of IT (Information and communication Technologies, ICT) with defense, as has already been achieved in civilian fields such as healthcare and construction. It is expected that completely new and common requirements would emerge from the civilian and military domains and that the shape of war field would change rapidly. Many military scientists forecast that future wars would be network-centric and be based on C4I(Command, Control, Communication & Computer, Intelligence), ISR(Intelligence, Surveillance & Reconnaissance), and PGM(Precision Guided Munitions). For realizing the smart defense concept, IT should act as a baseline technology even for simulating a real combat field using virtual reality. In this paper, we propose the concept of IT-based smart defense with a focus on accurate detection in real and cyber wars, effective data communication, automated and unmanned operation, and modeling and simulation.

A Study on Technological Forecasting of Next-Generation Display Technology (차세대 디스플레이 기술의 예측에 관한 연구)

  • Nam, Ki-Woong;Park, Sang-Sung;Shin, Young-Geun;Jung, Won-Gyo;Jang, Dong-Sik
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.10
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    • pp.2923-2934
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    • 2009
  • This paper presents study on technological forecasting of Next-Generation Display technology. Next-Generation Display technology is one of the emerging technologies lately. So databases on patent documents of this technology were analyzed first. And patent analysis was performed for finding out present technology trend. And the forecast for this technology was made by growth curves which were obtained from forecast models using patent documents. In previous study, Gompertz, Logistic, Bass were used for forecasting diffusion of demand in market. Gompertz, Logistic models which were often used for technological forecasting, too. So, two models were applied in this study. But Gompertz, Logistic models only consider internal effect of diffusion. And it is difficult to estimate maximum value of growth in two models. So, Bass model which considers both internal effect and external effect of diffusion was also applied. And maximum value of growth in Gompertz, Logistic models was estimated by Bass model.